From c545a8d2d195d62b8afa2fb592958e1921c82db5 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Tue, 29 Oct 2019 08:41:34 -0700 Subject: [PATCH 01/42] Updating Dockerfile innards --- Dockerfile | 20 +++++++++++++------- Dockerfile.template | 20 +++++++++++++------- 2 files changed, 26 insertions(+), 14 deletions(-) diff --git a/Dockerfile b/Dockerfile index 2c5c88e..7dd8696 100644 --- a/Dockerfile +++ b/Dockerfile @@ -3,18 +3,24 @@ FROM agpipeline/gantry-base-image:latest LABEL maintainer="Chris Schnaufer " -COPY configuration.py transformer.py requirements.txt packages.txt /home/extractor/ +COPY requirements.txt packages.txt /home/extractor/ USER root -RUN apt-get update && \ - cat /home/extractor/packages.txt | xargs apt-get install -y --no-install-recommends && \ - rm /home/extractor/packages.txt && \ - apt-get autoremove -y && \ - apt-get clean && \ - rm -rf /var/lib/apt/lists/* +RUN [ -s /home/extractor/packages.txt ] && \ + (echo 'Installing packages' && \ + apt-get update && \ + cat /home/extractor/packages.txt | xargs apt-get install -y --no-install-recommends && \ + rm /home/extractor/packages.txt && \ + apt-get autoremove -y && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/*) || \ + (echo 'No packages to install' && \ + rm /home/extractor/packages.txt) RUN python3 -m pip install --no-cache-dir -r /home/extractor/requirements.txt && \ rm /home/extractor/requirements.txt USER extractor + +COPY configuration.py transformer.py /home/extractor/ diff --git a/Dockerfile.template b/Dockerfile.template index a6f5307..b638123 100644 --- a/Dockerfile.template +++ b/Dockerfile.template @@ -3,18 +3,24 @@ FROM base-image LABEL maintainer="" -COPY configuration.py transformer.py requirements.txt packages.txt /home/extractor/ +COPY requirements.txt packages.txt /home/extractor/ USER root -RUN apt-get update && \ - cat /home/extractor/packages.txt | xargs apt-get install -y --no-install-recommends && \ - rm /home/extractor/packages.txt && \ - apt-get autoremove -y && \ - apt-get clean && \ - rm -rf /var/lib/apt/lists/* +RUN [ -s /home/extractor/packages.txt ] && \ + (echo 'Installing packages' && \ + apt-get update && \ + cat /home/extractor/packages.txt | xargs apt-get install -y --no-install-recommends && \ + rm /home/extractor/packages.txt && \ + apt-get autoremove -y && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/*) || \ + (echo 'No packages to install' && \ + rm /home/extractor/packages.txt) RUN python3 -m pip install --no-cache-dir -r /home/extractor/requirements.txt && \ rm /home/extractor/requirements.txt USER extractor + +COPY configuration.py transformer.py /home/extractor/ From 5df8262585a2fddf55010aea0b86307a6b0d9c92 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 11 Nov 2019 10:59:41 -0700 Subject: [PATCH 02/42] Update README, moved code to "private" class (#3) * Updating README * Minor changes * Fixed return type and 'hid' internal functions --- README.md | 30 +++ transformer.py | 535 +++++++++++++++++++++++++------------------------ 2 files changed, 308 insertions(+), 257 deletions(-) diff --git a/README.md b/README.md index 175575c..b174aa9 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,32 @@ # Transformer Soil Mask Masks out the soil in images + +### Sample Docker Command line +Below is a sample command line that shows how the soil mask Docker image could be run. +An explanation of the command line options used follows. +Be sure to read up on the [docker run](https://docs.docker.com/engine/reference/run/) command line for more information. + +```docker run --rm --mount "src=/home/test,target=/mnt,type=bind" agpipeline/soilmask:2.0 --working_space "/mnt" --metadata "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_metadata_cleaned.json" "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif" ``` + +This example command line assumes the source files are located in the `/home/test` folder of the local machine. +The name of the image to run is `agpipeline/soilmask:2.0`. + +We are using the same folder for the source files and the output files. +By using multiple `--mount` options, the source and output files can be separated. + +**Docker commands** \ +Everything between 'docker' and the name of the image are docker commands. + +- `run` indicates we want to run an image +- `--rm` automatically delete the image instance after it's run +- `--mount "src=/home/test,target=/mnt,type=bind"` mounts the `/home/test` folder to the `/mnt` folder of the running image + +We mount the `/home/test` folder to the running image to make files available to the software in the image. + +**Image's commands** \ +The command line parameters after the image name are passed to the software inside the image. +Note that the paths provided are relative to the running image (see the --mount option specified above). + +- `--working_space "/mnt"` specifies the folder to use as a workspace +- `--metadata "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_metadata.cleaned.json"` is the name of the source metadata to be cleaned +- `"/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif"` is the name of the image to mask \ No newline at end of file diff --git a/transformer.py b/transformer.py index 0c2ae02..e4569d8 100644 --- a/transformer.py +++ b/transformer.py @@ -23,249 +23,282 @@ MAX_PIXEL_VAL = 255 SMALL_AREA_THRESHOLD = 200 -def get_image_quality(imgfile: str) -> np.ndarray: - """Computes and returns the image score for the image file - Arguments: - imgfile: the name of the file to compute the score for - Returns: - The score for the image - """ - img = Image.open(imgfile) - img = np.array(img) - - nrmac = MAC(img, img, img) - - return nrmac - -def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: - """Generates an image with plants masked in. - Arguments: - color_img: RGB image to mask - kernel_size: masking kernel size - Return: - An RGB image with plants masked in - """ - r_channel = color_img[:, :, 2] - g_channel = color_img[:, :, 1] - b_channel = color_img[:, :, 0] - - sub_img = (g_channel.astype('int') - r_channel.astype('int') - 0) > 0 # normal: -2 - - mask = np.zeros_like(b_channel) - - mask[sub_img] = MAX_PIXEL_VAL - - blur = cv2.blur(mask, (kernel_size, kernel_size)) - pix = np.array(blur) - sub_mask = pix > 128 - - mask_1 = np.zeros_like(b_channel) - mask_1[sub_mask] = MAX_PIXEL_VAL - - return mask_1 - -def remove_small_area_mask(mask_img: np.ndarray, min_area_size: int) -> np.ndarray: - """Removes small anomalies in the mask - Arguments: - mask_img: the mask image to remove anomalies from - min_area_size: the size of anomalies to look for - Return: - A new mask image with the anomalies removed - """ - mask_array = mask_img > 0 - rel_array = morphology.remove_small_objects(mask_array, min_area_size) - - rel_img = np.zeros_like(mask_img) - rel_img[rel_array] = MAX_PIXEL_VAL - - return rel_img - -def remove_small_holes_mask(mask_img: np.ndarray, max_hole_size: int) -> np.ndarray: - """Removes small holes from the mask image - Arguments: - mask_image: the mask image to remove holes from - max_hole_size: the maximum size of holes to remove - Return: - A new mask image with the holes removed - """ - mask_array = mask_img > 0 - rel_array = morphology.remove_small_holes(mask_array, max_hole_size) - rel_img = np.zeros_like(mask_img) - rel_img[rel_array] = MAX_PIXEL_VAL - - return rel_img - -def saturated_pixel_classification(gray_img: np.ndarray, base_mask: np.ndarray, saturated_mask: np.ndarray, - dilate_size: int = 0) -> np.ndarray: - """Returns an image with pixes classified for masking - Arguments: - Returns: - A mask image with the pixels classified - """ - # add saturated area into basic mask - saturated_mask = morphology.binary_dilation(saturated_mask, morphology.diamond(dilate_size)) - - rel_img = np.zeros_like(gray_img) - rel_img[saturated_mask] = MAX_PIXEL_VAL - - label_img, num = morphology.label(rel_img, connectivity=2, return_num=True) - - rel_mask = base_mask - - for idx in range(1, num): - match = (label_img == idx) - - if np.sum(match) > 100000: # if the area is too large, do not add it into basic mask - continue - - if not (match & base_mask).any(): - continue - - rel_mask = rel_mask | match - - return rel_mask - -def over_saturation_pocess(rgb_img: np.ndarray, init_mask: np.ndarray, \ - threshold: int = SATURATE_THRESHOLD) -> np.ndarray: - """Removes over saturated areas from an image - Arguments: - rgb_image: the image to process - init_mask: - threshold: The saturation threshold value - Return: - A new image with over saturated pixels removed +class __internal__(): + """Class for functions intended for internal use only for this file """ - # connected component analysis for over saturation pixels - gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY) - - mask_over = gray_img > threshold - - mask_0 = gray_img < threshold - - src_mask_array = init_mask > 0 - - mask_1 = src_mask_array & mask_0 - - mask_1 = morphology.remove_small_objects(mask_1, SMALL_AREA_THRESHOLD) - - mask_over = morphology.remove_small_objects(mask_over, SMALL_AREA_THRESHOLD) - - rel_mask = saturated_pixel_classification(gray_img, mask_1, mask_over, 1) - rel_img = np.zeros_like(gray_img) - rel_img[rel_mask] = MAX_PIXEL_VAL - - return rel_img - -def gen_saturated_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: - """Generates a mask of over saturated pixels - Arguments: - img: the image to generate the mask from - kernel_size: the size of masking kernel - Returns: - The image mask of over saturated pixels - """ - bin_mask = gen_plant_mask(img, kernel_size) - bin_mask = remove_small_area_mask(bin_mask, - 500) # 500 is a parameter for number of pixels to be removed as small area - bin_mask = remove_small_holes_mask(bin_mask, - 300) # 300 is a parameter for number of pixels to be filled as small holes - - bin_mask = over_saturation_pocess(img, bin_mask, SATURATE_THRESHOLD) - - bin_mask = remove_small_holes_mask(bin_mask, 4000) - - return bin_mask - -def gen_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: - """Generated the mask for plants - Arguments: - img: the image used to mask in plants - kernel_size: the size of the image processing kernel - Return: - A new image mask - """ - bin_mask = gen_plant_mask(img, kernel_size) - bin_mask = remove_small_area_mask(bin_mask, SMALL_AREA_THRESHOLD) - bin_mask = remove_small_holes_mask(bin_mask, - 3000) # 3000 is a parameter for number of pixels to be filled as small holes - - return bin_mask - -def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: - """Applies the mask to the image - Arguments: - img: the source image to mask - bin_mask: the mask to apply to the image - Return: - A new image that had the mask applied - """ - rgb_mask = cv2.bitwise_and(img, img, mask=bin_mask) - - return rgb_mask - -def rgb2gray(rgb: np.ndarray) -> np.ndarray: - """Converts RGB image to grey scale - Arguments: - rgb: the image to convert - Return: - The greyscale image - """ - r_channel, g_channel, b_channel = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2] - gray = 0.2989 * r_channel + 0.5870 * g_channel + 0.1140 * b_channel - return gray - -def MAC(im1: np.ndarray, im2: np.ndarray, im: np.ndarray) -> np.ndarray: # pylint: disable=invalid-name - """Calculates an image score of Multiscale Autocorrelation (MAC) - Arguments: - Return: - Returns the scored image - """ - h_dim, _, c_dim = im1.shape - if c_dim > 1: - im = np.matrix.round(rgb2gray(im)) - im1 = np.matrix.round(rgb2gray(im1)) - im2 = np.matrix.round(rgb2gray(im2)) - # multiscale parameters - scales = np.array([2, 3, 5]) - fm_arr = np.zeros(len(scales)) - for idx, _ in enumerate(scales): - im1[0: h_dim - 1, :] = im[1:h_dim, :] - im2[0: h_dim - scales[idx], :] = im[scales[idx]:h_dim, :] - dif = im * (im1 - im2) - fm_arr[idx] = np.mean(dif) - nrmac = np.mean(fm_arr) - return nrmac - -def check_saturation(img: np.ndarray) -> list: - """Checks the saturation of an image - Arguments: - img: the image to check - Return: - A list containing the over threshold rate and the under threshold rate - """ - # check how many percent of pix close to 255 or 0 - gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - - over_threshold = gray_img > SATURATE_THRESHOLD - under_threshold = gray_img < 20 # 20 is a threshold to classify low pixel value - - over_rate = float(np.sum(over_threshold)) / float(gray_img.size) - low_rate = float(np.sum(under_threshold)) / float(gray_img.size) - - return over_rate, low_rate - -def check_brightness(img: np.ndarray) -> float: - """Generates average pixel value from grayscale image - Arguments: - img: the source image - Returns: - The average pixel value of the image - """ - gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + def __init__(self): + """Performs initialization of class instance + """ + + @staticmethod + def get_image_quality(imgfile: str) -> np.ndarray: + """Computes and returns the image score for the image file + Arguments: + imgfile: the name of the file to compute the score for + Returns: + The score for the image + """ + img = Image.open(imgfile) + img = np.array(img) + + nrmac = __internal__.MAC(img, img, img) + + return nrmac + + @staticmethod + def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: + """Generates an image with plants masked in. + Arguments: + color_img: RGB image to mask + kernel_size: masking kernel size + Return: + An RGB image with plants masked in + """ + r_channel = color_img[:, :, 2] + g_channel = color_img[:, :, 1] + b_channel = color_img[:, :, 0] + + sub_img = (g_channel.astype('int') - r_channel.astype('int') - 0) > 0 # normal: -2 + + mask = np.zeros_like(b_channel) + + mask[sub_img] = MAX_PIXEL_VAL + + blur = cv2.blur(mask, (kernel_size, kernel_size)) + pix = np.array(blur) + sub_mask = pix > 128 + + mask_1 = np.zeros_like(b_channel) + mask_1[sub_mask] = MAX_PIXEL_VAL + + return mask_1 + + @staticmethod + def remove_small_area_mask(mask_img: np.ndarray, min_area_size: int) -> np.ndarray: + """Removes small anomalies in the mask + Arguments: + mask_img: the mask image to remove anomalies from + min_area_size: the size of anomalies to look for + Return: + A new mask image with the anomalies removed + """ + mask_array = mask_img > 0 + rel_array = morphology.remove_small_objects(mask_array, min_area_size) + + rel_img = np.zeros_like(mask_img) + rel_img[rel_array] = MAX_PIXEL_VAL + + return rel_img + + @staticmethod + def remove_small_holes_mask(mask_img: np.ndarray, max_hole_size: int) -> np.ndarray: + """Removes small holes from the mask image + Arguments: + mask_image: the mask image to remove holes from + max_hole_size: the maximum size of holes to remove + Return: + A new mask image with the holes removed + """ + mask_array = mask_img > 0 + rel_array = morphology.remove_small_holes(mask_array, max_hole_size) + rel_img = np.zeros_like(mask_img) + rel_img[rel_array] = MAX_PIXEL_VAL + + return rel_img + + @staticmethod + def saturated_pixel_classification(gray_img: np.ndarray, base_mask: np.ndarray, saturated_mask: np.ndarray, + dilate_size: int = 0) -> np.ndarray: + """Returns an image with pixes classified for masking + Arguments: + Returns: + A mask image with the pixels classified + """ + # add saturated area into basic mask + saturated_mask = morphology.binary_dilation(saturated_mask, morphology.diamond(dilate_size)) + + rel_img = np.zeros_like(gray_img) + rel_img[saturated_mask] = MAX_PIXEL_VAL + + label_img, num = morphology.label(rel_img, connectivity=2, return_num=True) + + rel_mask = base_mask + + for idx in range(1, num): + match = (label_img == idx) + + if np.sum(match) > 100000: # if the area is too large, do not add it into basic mask + continue - avg_value = np.average(gray_img) + if not (match & base_mask).any(): + continue - return avg_value + rel_mask = rel_mask | match + + return rel_mask + + @staticmethod + def over_saturation_pocess(rgb_img: np.ndarray, init_mask: np.ndarray, \ + threshold: int = SATURATE_THRESHOLD) -> np.ndarray: + """Removes over saturated areas from an image + Arguments: + rgb_image: the image to process + init_mask: + threshold: The saturation threshold value + Return: + A new image with over saturated pixels removed + """ + # connected component analysis for over saturation pixels + gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY) + + mask_over = gray_img > threshold + + mask_0 = gray_img < threshold + + src_mask_array = init_mask > 0 + + mask_1 = src_mask_array & mask_0 + + mask_1 = morphology.remove_small_objects(mask_1, SMALL_AREA_THRESHOLD) + + mask_over = morphology.remove_small_objects(mask_over, SMALL_AREA_THRESHOLD) + + rel_mask = __internal__.saturated_pixel_classification(gray_img, mask_1, mask_over, 1) + rel_img = np.zeros_like(gray_img) + rel_img[rel_mask] = MAX_PIXEL_VAL + + return rel_img + + @staticmethod + def gen_saturated_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: + """Generates a mask of over saturated pixels + Arguments: + img: the image to generate the mask from + kernel_size: the size of masking kernel + Returns: + The image mask of over saturated pixels + """ + bin_mask = __internal__.gen_plant_mask(img, kernel_size) + bin_mask = __internal__.remove_small_area_mask(bin_mask, + 500) # 500 is a parameter for number of pixels to be removed as small area + bin_mask = __internal__.remove_small_holes_mask(bin_mask, + 300) # 300 is a parameter for number of pixels to be filled as small holes + + bin_mask = __internal__.over_saturation_pocess(img, bin_mask, SATURATE_THRESHOLD) + + bin_mask = __internal__.remove_small_holes_mask(bin_mask, 4000) + + return bin_mask + + @staticmethod + def gen_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: + """Generated the mask for plants + Arguments: + img: the image used to mask in plants + kernel_size: the size of the image processing kernel + Return: + A new image mask + """ + bin_mask = __internal__.gen_plant_mask(img, kernel_size) + bin_mask = __internal__.remove_small_area_mask(bin_mask, SMALL_AREA_THRESHOLD) + bin_mask = __internal__.remove_small_holes_mask(bin_mask, + 3000) # 3000 is a parameter for number of pixels to be filled as small holes + + return bin_mask + + @staticmethod + def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: + """Applies the mask to the image + Arguments: + img: the source image to mask + bin_mask: the mask to apply to the image + Return: + A new image that had the mask applied + """ + rgb_mask = cv2.bitwise_and(img, img, mask=bin_mask) + + return rgb_mask + + @staticmethod + def rgb2gray(rgb: np.ndarray) -> np.ndarray: + """Converts RGB image to grey scale + Arguments: + rgb: the image to convert + Return: + The greyscale image + """ + r_channel, g_channel, b_channel = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2] + gray = 0.2989 * r_channel + 0.5870 * g_channel + 0.1140 * b_channel + return gray + + @staticmethod + def MAC(im1: np.ndarray, im2: np.ndarray, im: np.ndarray) -> np.ndarray: # pylint: disable=invalid-name + """Calculates an image score of Multiscale Autocorrelation (MAC) + Arguments: + Return: + Returns the scored image + """ + h_dim, _, c_dim = im1.shape + if c_dim > 1: + im = np.matrix.round(__internal__.rgb2gray(im)) + im1 = np.matrix.round(__internal__.rgb2gray(im1)) + im2 = np.matrix.round(__internal__.rgb2gray(im2)) + # multiscale parameters + scales = np.array([2, 3, 5]) + fm_arr = np.zeros(len(scales)) + for idx, _ in enumerate(scales): + im1[0: h_dim - 1, :] = im[1:h_dim, :] + im2[0: h_dim - scales[idx], :] = im[scales[idx]:h_dim, :] + dif = im * (im1 - im2) + fm_arr[idx] = np.mean(dif) + nrmac = np.mean(fm_arr) + return nrmac + + @staticmethod + def check_saturation(img: np.ndarray) -> list: + """Checks the saturation of an image + Arguments: + img: the image to check + Return: + A list containing the over threshold rate and the under threshold rate + """ + # check how many percent of pix close to 255 or 0 + gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + + over_threshold = gray_img > SATURATE_THRESHOLD + under_threshold = gray_img < 20 # 20 is a threshold to classify low pixel value + + over_rate = float(np.sum(over_threshold)) / float(gray_img.size) + low_rate = float(np.sum(under_threshold)) / float(gray_img.size) + + return over_rate, low_rate + + @staticmethod + def check_brightness(img: np.ndarray) -> float: + """Generates average pixel value from grayscale image + Arguments: + img: the source image + Returns: + The average pixel value of the image + """ + gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + + avg_value = np.average(gray_img) + + return avg_value + + @staticmethod + def get_maskfilename(filename: str) -> str: + """Returns the name of the file to use as a mask. Any path information + in the filename parameter is not returned. + Arguments: + filename: the name of the file to convert to a mask name + Return: + The name of the mask file + """ + base, ext = os.path.splitext(os.path.basename(filename)) + + return base + "_mask" + ext def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: """Generates an image mask keeping plants @@ -283,7 +316,7 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: # calculate image scores # pylint: disable=unused-variable - over_rate, low_rate = check_saturation(img) + over_rate, low_rate = __internal__.check_saturation(img) # TODO: disabling this check for now because it's crashing extractor - generate mask regardless # if low score, return None @@ -300,29 +333,17 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: # over_rate is percentage of high value pixels(higher than SATUTATE_THRESHOLD) in the grayscale image, if # over_rate > 0.15, try to fix it use gen_saturated_mask() if over_rate > 0.15: - bin_mask = gen_saturated_mask(img, kernel_size) + bin_mask = __internal__.gen_saturated_mask(img, kernel_size) else: # nomal image process - bin_mask = gen_mask(img, kernel_size) + bin_mask = __internal__.gen_mask(img, kernel_size) count = np.count_nonzero(bin_mask) ratio = count / float(bin_mask.size) - rgb_mask = gen_rgb_mask(img, bin_mask) + rgb_mask = __internal__.gen_rgb_mask(img, bin_mask) return ratio, rgb_mask -def get_maskfilename(filename: str) -> str: - """Returns the name of the file to use as a mask. Any path information - in the filename parameter is not returned. - Arguments: - filename: the name of the file to convert to a mask name - Return: - The name of the mask file - """ - base, ext = os.path.splitext(os.path.basename(filename)) - - return base + "_mask" + ext - def check_continue(transformer: transformer_class.Transformer, check_md: dict, transformer_md: dict, full_md: dict) -> list: """Checks if conditions are right for continuing processing @@ -406,7 +427,7 @@ def perform_process(transformer: transformer_class.Transformer, check_md: dict, continue # Get the mask name using the original name as reference - rgb_mask_tif = os.path.join(check_md['working_folder'], get_maskfilename(one_file)) + rgb_mask_tif = os.path.join(check_md['working_folder'], __internal__.get_maskfilename(one_file)) # Create the mask file logging.debug("Creating mask file '%s'", rgb_mask_tif) From e3ea916ecd6637287ac1bcc46d39cf93ee744f77 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Tue, 14 Jan 2020 09:19:30 -0700 Subject: [PATCH 03/42] Fixed typos and expanded README (#6) * Reconciling return types * Adding in some Drone related changes --- .dockerignore | 1 + README.md | 17 ++++++++++++++++- transformer.py | 10 +++++----- 3 files changed, 22 insertions(+), 6 deletions(-) create mode 100644 .dockerignore diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000..9daeafb --- /dev/null +++ b/.dockerignore @@ -0,0 +1 @@ +test diff --git a/README.md b/README.md index b174aa9..b529174 100644 --- a/README.md +++ b/README.md @@ -29,4 +29,19 @@ Note that the paths provided are relative to the running image (see the --mount - `--working_space "/mnt"` specifies the folder to use as a workspace - `--metadata "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_metadata.cleaned.json"` is the name of the source metadata to be cleaned -- `"/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif"` is the name of the image to mask \ No newline at end of file +- `"/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif"` is the name of the image to mask + +## Transformer class dependencies +This transformer has the following requirements from the [Environmental](https://github.com/AgPipeline/AgPipeline.github.io/blob/transformers/transformers/transformers.md) Transformer class. + +Expected method signatures and explanations: +- **get_image_file_epsg(file_name: str) -> str**: function returns the EPSG code from a georeferenced image file, or None +- **default_epsg -> str**: property returning the expected EPSG; compared against a file's EPSG code to determine if the resulting mask file needs to be converted to match the default EPSG +- **get_image_file_geobounds(file_name: str) -> list**: function returns the geographic boundaries of a georeferenced image file as a list ordered as [min_y, max_y, min_x, max_x] or a list of four numpy.nan values if the file is not georeferenced +- **generate_transformer_md() -> dict**: function returns a dictionary with the following minimum set of keys: + - `name`: the name of the transformer (the configuration.py file can be used for this) + - `version`: the version of the transformer (the configuration.py file can be used for this) + - `author`: the author of the transformer (the configuration.py file can be used for this) + - `description`: the description of the transformer (the configuration.py file can be used for this) + - `repository`: optional repository URI of transformer source code (the configuration.py file can be used for this) + \ No newline at end of file diff --git a/transformer.py b/transformer.py index e4569d8..3a347e1 100644 --- a/transformer.py +++ b/transformer.py @@ -345,7 +345,7 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: return ratio, rgb_mask def check_continue(transformer: transformer_class.Transformer, check_md: dict, transformer_md: dict, - full_md: dict) -> list: + full_md: dict) -> tuple: """Checks if conditions are right for continuing processing Arguments: transformer: instance of transformer class @@ -353,11 +353,11 @@ def check_continue(transformer: transformer_class.Transformer, check_md: dict, t transformer_md: the metadata associated with this transformer full_md: the full set of original metadata Return: - Returns a dictionary containining the return code for continuing or not, and + Returns a tuple containing the return code for continuing or not, and an error message if there's an error """ # pylint: disable=unused-argument - result = {} + result = {'code': -2, 'message': "No TIFF files were specified for processing"} # Ensure we have a TIFF file if check_md and 'list_files' in check_md: @@ -402,7 +402,7 @@ def perform_process(transformer: transformer_class.Transformer, check_md: dict, mask_source = one_file # Get the image's EPSG code - epsg = tr_get_epsg(mask_source) + epsg = transformer.get_image_file_epsg(mask_source) if epsg is None: logging.debug("Skipping image that is not georeferenced: '%s'", mask_source) continue @@ -417,7 +417,7 @@ def perform_process(transformer: transformer_class.Transformer, check_md: dict, mask_source = tmp_name # Get the bounds of the image to see if we can process it. - bounds = tr_image_get_geobounds(mask_source) + bounds = transformer.get_image_file_geobounds(mask_source) if bounds is None: logging.warning("Unable to get bounds of georeferenced image: '%s'", From 65197cfdfc28b425f2dba057a023b5b3cb130c2f Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Fri, 31 Jan 2020 10:55:22 -0700 Subject: [PATCH 04/42] Commented our unused code, fixed parameter types, other minor changes (#9) --- Dockerfile | 10 ++- transformer.py | 172 +++++++++++++++++++++++++------------------------ 2 files changed, 96 insertions(+), 86 deletions(-) diff --git a/Dockerfile b/Dockerfile index 7dd8696..f107ccf 100644 --- a/Dockerfile +++ b/Dockerfile @@ -18,8 +18,14 @@ RUN [ -s /home/extractor/packages.txt ] && \ (echo 'No packages to install' && \ rm /home/extractor/packages.txt) -RUN python3 -m pip install --no-cache-dir -r /home/extractor/requirements.txt && \ - rm /home/extractor/requirements.txt +RUN [ -s /home/extractor/requirements.txt ] && \ + (echo "Install python modules" && \ + python3 -m pip install -U --no-cache-dir pip && \ + python3 -m pip install --no-cache-dir setuptools && \ + python3 -m pip install --no-cache-dir -r /home/extractor/requirements.txt && \ + rm /home/extractor/requirements.txt) || \ + (echo "No python modules to install" && \ + rm /home/extractor/requirements.txt) USER extractor diff --git a/transformer.py b/transformer.py index 3a347e1..66aedee 100644 --- a/transformer.py +++ b/transformer.py @@ -8,13 +8,11 @@ import cv2 from osgeo import gdal -from PIL import Image +# from PIL import Image Used by code that's getting deprecated from skimage import morphology from terrautils.formats import create_geotiff as tr_create_geotiff, \ compress_geotiff as tr_compress_geotiff -from terrautils.imagefile import get_epsg as tr_get_epsg, \ - image_get_geobounds as tr_image_get_geobounds import configuration import transformer_class @@ -23,6 +21,7 @@ MAX_PIXEL_VAL = 255 SMALL_AREA_THRESHOLD = 200 + class __internal__(): """Class for functions intended for internal use only for this file """ @@ -30,20 +29,20 @@ def __init__(self): """Performs initialization of class instance """ - @staticmethod - def get_image_quality(imgfile: str) -> np.ndarray: - """Computes and returns the image score for the image file - Arguments: - imgfile: the name of the file to compute the score for - Returns: - The score for the image - """ - img = Image.open(imgfile) - img = np.array(img) - - nrmac = __internal__.MAC(img, img, img) - - return nrmac +# @staticmethod +# def get_image_quality(imgfile: str) -> np.ndarray: +# """Computes and returns the image score for the image file +# Arguments: +# imgfile: the name of the file to compute the score for +# Returns: +# The score for the image +# """ +# img = Image.open(imgfile) +# img = np.array(img) +# +# nrmac = __internal__.MAC(img, img, img) +# +# return nrmac @staticmethod def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: @@ -91,7 +90,7 @@ def remove_small_area_mask(mask_img: np.ndarray, min_area_size: int) -> np.ndarr return rel_img @staticmethod - def remove_small_holes_mask(mask_img: np.ndarray, max_hole_size: int) -> np.ndarray: + def remove_small_holes_mask(mask_image: np.ndarray, max_hole_size: int) -> np.ndarray: """Removes small holes from the mask image Arguments: mask_image: the mask image to remove holes from @@ -99,9 +98,9 @@ def remove_small_holes_mask(mask_img: np.ndarray, max_hole_size: int) -> np.ndar Return: A new mask image with the holes removed """ - mask_array = mask_img > 0 + mask_array = mask_image > 0 rel_array = morphology.remove_small_holes(mask_array, max_hole_size) - rel_img = np.zeros_like(mask_img) + rel_img = np.zeros_like(mask_image) rel_img[rel_array] = MAX_PIXEL_VAL return rel_img @@ -138,8 +137,7 @@ def saturated_pixel_classification(gray_img: np.ndarray, base_mask: np.ndarray, return rel_mask @staticmethod - def over_saturation_pocess(rgb_img: np.ndarray, init_mask: np.ndarray, \ - threshold: int = SATURATE_THRESHOLD) -> np.ndarray: + def over_saturation_process(rgb_image: np.ndarray, init_mask: np.ndarray, threshold: int = SATURATE_THRESHOLD) -> np.ndarray: """Removes over saturated areas from an image Arguments: rgb_image: the image to process @@ -149,7 +147,7 @@ def over_saturation_pocess(rgb_img: np.ndarray, init_mask: np.ndarray, \ A new image with over saturated pixels removed """ # connected component analysis for over saturation pixels - gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY) + gray_img = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY) mask_over = gray_img > threshold @@ -184,7 +182,7 @@ def gen_saturated_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: bin_mask = __internal__.remove_small_holes_mask(bin_mask, 300) # 300 is a parameter for number of pixels to be filled as small holes - bin_mask = __internal__.over_saturation_pocess(img, bin_mask, SATURATE_THRESHOLD) + bin_mask = __internal__.over_saturation_process(img, bin_mask, SATURATE_THRESHOLD) bin_mask = __internal__.remove_small_holes_mask(bin_mask, 4000) @@ -219,40 +217,40 @@ def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: return rgb_mask - @staticmethod - def rgb2gray(rgb: np.ndarray) -> np.ndarray: - """Converts RGB image to grey scale - Arguments: - rgb: the image to convert - Return: - The greyscale image - """ - r_channel, g_channel, b_channel = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2] - gray = 0.2989 * r_channel + 0.5870 * g_channel + 0.1140 * b_channel - return gray - - @staticmethod - def MAC(im1: np.ndarray, im2: np.ndarray, im: np.ndarray) -> np.ndarray: # pylint: disable=invalid-name - """Calculates an image score of Multiscale Autocorrelation (MAC) - Arguments: - Return: - Returns the scored image - """ - h_dim, _, c_dim = im1.shape - if c_dim > 1: - im = np.matrix.round(__internal__.rgb2gray(im)) - im1 = np.matrix.round(__internal__.rgb2gray(im1)) - im2 = np.matrix.round(__internal__.rgb2gray(im2)) - # multiscale parameters - scales = np.array([2, 3, 5]) - fm_arr = np.zeros(len(scales)) - for idx, _ in enumerate(scales): - im1[0: h_dim - 1, :] = im[1:h_dim, :] - im2[0: h_dim - scales[idx], :] = im[scales[idx]:h_dim, :] - dif = im * (im1 - im2) - fm_arr[idx] = np.mean(dif) - nrmac = np.mean(fm_arr) - return nrmac +# @staticmethod +# def rgb2gray(rgb: np.ndarray) -> np.ndarray: +# """Converts RGB image to grey scale +# Arguments: +# rgb: the image to convert +# Return: +# The greyscale image +# """ +# r_channel, g_channel, b_channel = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2] +# gray = 0.2989 * r_channel + 0.5870 * g_channel + 0.1140 * b_channel +# return gray + +# @staticmethod +# def MAC(im1: np.ndarray, im2: np.ndarray, im: np.ndarray) -> np.ndarray: # pylint: disable=invalid-name +# """Calculates an image score of Multiscale Autocorrelation (MAC) +# Arguments: +# Return: +# Returns the scored image +# """ +# h_dim, _, c_dim = im1.shape +# if c_dim > 1: +# im = np.matrix.round(__internal__.rgb2gray(im)) +# im1 = np.matrix.round(__internal__.rgb2gray(im1)) +# im2 = np.matrix.round(__internal__.rgb2gray(im2)) +# # multiscale parameters +# scales = np.array([2, 3, 5]) +# fm_arr = np.zeros(len(scales)) +# for idx, _ in enumerate(scales): +# im1[0: h_dim - 1, :] = im[1:h_dim, :] +# im2[0: h_dim - scales[idx], :] = im[scales[idx]:h_dim, :] +# dif = im * (im1 - im2) +# fm_arr[idx] = np.mean(dif) +# nrmac = np.mean(fm_arr) +# return nrmac @staticmethod def check_saturation(img: np.ndarray) -> list: @@ -273,19 +271,19 @@ def check_saturation(img: np.ndarray) -> list: return over_rate, low_rate - @staticmethod - def check_brightness(img: np.ndarray) -> float: - """Generates average pixel value from grayscale image - Arguments: - img: the source image - Returns: - The average pixel value of the image - """ - gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - - avg_value = np.average(gray_img) - - return avg_value +# @staticmethod +# def check_brightness(img: np.ndarray) -> float: +# """Generates average pixel value from grayscale image +# Arguments: +# img: the source image +# Returns: +# The average pixel value of the image +# """ +# gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) +# +# avg_value = np.average(gray_img) +# +# return avg_value @staticmethod def get_maskfilename(filename: str) -> str: @@ -300,7 +298,8 @@ def get_maskfilename(filename: str) -> str: return base + "_mask" + ext -def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: + +def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> tuple: """Generates an image mask keeping plants Arguments: input_path: the path to the input image @@ -324,17 +323,17 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: # aveValue is average pixel value of grayscale image, if aveValue lower than 30 or higher than 195, return # quality_score is a score from Multiscale Autocorrelation (MAC), if quality_score lower than 13, return - #aveValue = check_brightness(img) - #quality_score = get_image_quality(input_path) - #if low_rate > 0.1 or aveValue < 30 or aveValue > 195 or quality_score < 13: + # saveValue = check_brightness(img) + # quality_score = get_image_quality(input_path) + # if low_rate > 0.1 or aveValue < 30 or aveValue > 195 or quality_score < 13: # return None, None, None # saturated image process - # over_rate is percentage of high value pixels(higher than SATUTATE_THRESHOLD) in the grayscale image, if + # over_rate is percentage of high value pixels(higher than SATURATE_THRESHOLD) in the grayscale image, if # over_rate > 0.15, try to fix it use gen_saturated_mask() if over_rate > 0.15: bin_mask = __internal__.gen_saturated_mask(img, kernel_size) - else: # nomal image process + else: # normal image process bin_mask = __internal__.gen_mask(img, kernel_size) count = np.count_nonzero(bin_mask) @@ -344,8 +343,9 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> list: return ratio, rgb_mask -def check_continue(transformer: transformer_class.Transformer, check_md: dict, transformer_md: dict, - full_md: dict) -> tuple: + +def check_continue(transformer: transformer_class.Transformer, check_md: dict, transformer_md: list, + full_md: list) -> tuple: """Checks if conditions are right for continuing processing Arguments: transformer: instance of transformer class @@ -357,7 +357,7 @@ def check_continue(transformer: transformer_class.Transformer, check_md: dict, t an error message if there's an error """ # pylint: disable=unused-argument - result = {'code': -2, 'message': "No TIFF files were specified for processing"} + result = {'code': -1002, 'message': "No TIFF files were specified for processing"} # Ensure we have a TIFF file if check_md and 'list_files' in check_md: @@ -377,8 +377,9 @@ def check_continue(transformer: transformer_class.Transformer, check_md: dict, t return (result['code'], result['error']) if 'error' in result else (result['code']) -def perform_process(transformer: transformer_class.Transformer, check_md: dict, transformer_md: dict, - full_md: dict) -> dict: + +def perform_process(transformer: transformer_class.Transformer, check_md: dict, transformer_md: list, + full_md: list) -> dict: """Performs the processing of the data Arguments: transformer: instance of transformer class' @@ -397,7 +398,10 @@ def perform_process(transformer: transformer_class.Transformer, check_md: dict, for one_file in check_md['list_files'](): # Check file by type ext = os.path.splitext(one_file)[1].lower() - if not ext in ('.tiff', '.tif'): + if ext not in ('.tiff', '.tif'): + continue + if not os.path.exists(one_file): + logging.warning("Unable to access file '%s'", one_file) continue mask_source = one_file @@ -464,7 +468,7 @@ def perform_process(transformer: transformer_class.Transformer, check_md: dict, result['file'] = file_md except Exception as ex: - result['code'] = -1 + result['code'] = -1001 result['error'] = "Exception caught masking files: %s" % str(ex) return result From 1b7abf5735d121e8db396dfdd71eeb215999e352 Mon Sep 17 00:00:00 2001 From: David LeBauer Date: Wed, 1 Apr 2020 14:31:37 -0700 Subject: [PATCH 05/42] Tried to update algorithm copied from the transformer-soilmask repository and updated based on code in based on code on transformer.py --- README.md | 61 +++++++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 59 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index b529174..37931d8 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,62 @@ # Transformer Soil Mask -Masks out the soil in images + +Converts an RGB image into a soil mask in which the soil is represented as black. + +The core idea for this Transformer is a plant-soil segmentation. + +## Algorithm Description + +The core idea for this Transformer is a plant-soil segmentation. We apply a threshold to differentiate plant and soil, and do a smoothing after binary processing. Saturated portions of the image are removed. At the end, it returns the plant area ratio (canopy cover) within a bounding box. + +Steps: + +1. Split image data into R,G,B channel, and make a tmp image. +2. For each pixel, if G value is T(threshold) higher than R value, make this pixel as foreground, and set the tmp pixel value to 255, so all tmp pixels are 0 or 255. +3. Use a filter to blur this tmp image +4. Remove anomalies (small areas incorrectly classified as plant of interest) +4. Threshold the blurred tmp image with a threshold of 128 to get a new mask image that represents our plant (foreground) detections. +5. Remove saturated pixels +5. Output ratio = foreground pixel count / total pixel count + +### Parameters + +* G - R Threshold is set to 2 for normal situation. +* Blur: image to new mask threshold is set to 128; passed to the OpenCV blur function. +* Saturation threshold: threshold for classifying a pixel as saturated. Default is 245 in a greyscale imagess +* Small Area Threshold: Used to remove anomalies from the image - this parameter is the size of a mask fragment in pixels that is removed. + +### Quality Statement + +Currently, this algorithm has been used on wheat and sorghum; it has been tested on lettuce but only works when the leaves are green (fails if they are red or purple). + +We believe the tested threshold works well in a normal illumination. Below are three examples of successful segmentation: + +![cc1](figures/normal_canopy_cover.png) +![cc2](figures/normal_canopy_cover2.png) + +![cc3](figures/normal_canopy_cover3.png) + +At the same time, there are some limitations with the current threshold. Here are some examples: + +1. Image captured in a low illumination. + +![2016-10-07__03-06-00-741](figures/low_illumination.jpg) + +2. Image captured in a very high illumination. + +![2016-09-28__12-19-06-452](figures/high_illumination.jpg) + +3. In late season, panicle is covering a lot in the image, and leaves is getting yellow. + +![2016-11-15__09-45-50-604](figures/yellow_plant.jpg) + +4. Sometimes an unidentified sensor problem results in a blank image. + +![2016-10-10__11-04-18-165](figures/sensor_problem.jpg) + +For more details, see related discussions, including: https://github.com/terraref/reference-data/issues/186#issuecomment-333631648 + + ### Sample Docker Command line Below is a sample command line that shows how the soil mask Docker image could be run. @@ -44,4 +101,4 @@ Expected method signatures and explanations: - `author`: the author of the transformer (the configuration.py file can be used for this) - `description`: the description of the transformer (the configuration.py file can be used for this) - `repository`: optional repository URI of transformer source code (the configuration.py file can be used for this) - \ No newline at end of file + From 7f8d63ed3f31d66d94c9a058633a8001b3b4b7f6 Mon Sep 17 00:00:00 2001 From: David LeBauer Date: Thu, 2 Apr 2020 10:33:02 -0700 Subject: [PATCH 06/42] moved figures from canopy cover repository to soilmask 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    y?&{LwTPyo_ zmKj<%c!k8cLP5!1PaQcvwd$X;m4q74$Dannc?>sD>KcT07fCV+7Utc~$A!V+qh%#Z z9D)uA#dp(_gXXF4a_xVbe}AEzn@L#tP7jB%&i?>C#L{G8glV*6*T3==tKqMPZLI67 zW2Wim^5R8#Jh`OY?5Ks?fw!WmJu}5?*j!09+;KdP(X))9Y^mgSsjS%A>9XBJj*$tyBi!5SvWqXgj*a&V&nWZ-jLPlTMyWpK<(H=M&KlYpy=%L`HaK6lsk zdwjMkwLV^_GvVEP><7t`Nc_Hu=8yp%fboyOitTh)h8B)yhT_+7%E=s~&){o- z)ZjtlE5+EmR^h-H>B+4x53&19apd`BxliFgFzsDZS64An(&uq|s_2uQvTBk>N##si zzXC%aAn>C^_wtx4Ri?yz5&POPf;ajq0IQw{{ZaXA(kY} zfS;LJiBtr113!*OudZr)2_n(7)tYEkldj+32ZNS9Pf=N(Am>!MJ=)>PKEE-o%}Eu! zEjCmi^tWC|Zzet~R_u}=E!js%)aLOIizB*{;7M?LW{J;7YPyD>Gr!Ts98t=m`KU}!8 zy|&e@t>M0mU959L;Rr4BC}j*XtQkl+wLjhPo?94W{Av(0T>v28LoB$o9( qdJ3l5GL4K|-w$~%f6?Yx{TTHAR8*6w@?U|# Date: Thu, 2 Apr 2020 10:38:29 -0700 Subject: [PATCH 07/42] removed the transformer class dependencies section from readme --- README.md | 17 +---------------- 1 file changed, 1 insertion(+), 16 deletions(-) diff --git a/README.md b/README.md index 37931d8..b17448f 100644 --- a/README.md +++ b/README.md @@ -56,9 +56,8 @@ At the same time, there are some limitations with the current threshold. Here ar For more details, see related discussions, including: https://github.com/terraref/reference-data/issues/186#issuecomment-333631648 - - ### Sample Docker Command line + Below is a sample command line that shows how the soil mask Docker image could be run. An explanation of the command line options used follows. Be sure to read up on the [docker run](https://docs.docker.com/engine/reference/run/) command line for more information. @@ -88,17 +87,3 @@ Note that the paths provided are relative to the running image (see the --mount - `--metadata "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_metadata.cleaned.json"` is the name of the source metadata to be cleaned - `"/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif"` is the name of the image to mask -## Transformer class dependencies -This transformer has the following requirements from the [Environmental](https://github.com/AgPipeline/AgPipeline.github.io/blob/transformers/transformers/transformers.md) Transformer class. - -Expected method signatures and explanations: -- **get_image_file_epsg(file_name: str) -> str**: function returns the EPSG code from a georeferenced image file, or None -- **default_epsg -> str**: property returning the expected EPSG; compared against a file's EPSG code to determine if the resulting mask file needs to be converted to match the default EPSG -- **get_image_file_geobounds(file_name: str) -> list**: function returns the geographic boundaries of a georeferenced image file as a list ordered as [min_y, max_y, min_x, max_x] or a list of four numpy.nan values if the file is not georeferenced -- **generate_transformer_md() -> dict**: function returns a dictionary with the following minimum set of keys: - - `name`: the name of the transformer (the configuration.py file can be used for this) - - `version`: the version of the transformer (the configuration.py file can be used for this) - - `author`: the author of the transformer (the configuration.py file can be used for this) - - `description`: the description of the transformer (the configuration.py file can be used for this) - - `repository`: optional repository URI of transformer source code (the configuration.py file can be used for this) - From 5ee04fb77025fabdaf9bb9f2cc48ab4c836f12db Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Mon, 20 Apr 2020 17:31:11 -0700 Subject: [PATCH 08/42] WIP: SCIF recipe for soilmask transformer --- .gitignore | 3 +- Dockerfile | 43 ++--- entrypoint.py | 409 +++++++++++++++++++++++++++++++++++++++++++ recipe.scif | 7 + transformer_class.py | 261 +++++++++++++++++++++++++++ 5 files changed, 693 insertions(+), 30 deletions(-) create mode 100755 entrypoint.py create mode 100644 recipe.scif create mode 100644 transformer_class.py diff --git a/.gitignore b/.gitignore index 905985e..e2aeb1c 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ .idea/* -*.pyc \ No newline at end of file +*.pyc +test \ No newline at end of file diff --git a/Dockerfile b/Dockerfile index f107ccf..44a4baf 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,32 +1,17 @@ -# Version 1.0 template-transformer-simple +#FROM phusion/baseimage +FROM agdrone/transformer-opendronemap:3.0 +# Env variables +ENV DEBIAN_FRONTEND noninteractive -FROM agpipeline/gantry-base-image:latest -LABEL maintainer="Chris Schnaufer " +COPY transformer_class.py configuration.py entrypoint.py /scif/apps/soilmask/src/ +COPY transformer.py /scif/apps/soilmask/src/ +# Install the filesystem from the recipe +COPY *.scif / +RUN scif install /recipe.scif -COPY requirements.txt packages.txt /home/extractor/ +# Cleanup APT +#RUN apt-get clean \ +# && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* -USER root - -RUN [ -s /home/extractor/packages.txt ] && \ - (echo 'Installing packages' && \ - apt-get update && \ - cat /home/extractor/packages.txt | xargs apt-get install -y --no-install-recommends && \ - rm /home/extractor/packages.txt && \ - apt-get autoremove -y && \ - apt-get clean && \ - rm -rf /var/lib/apt/lists/*) || \ - (echo 'No packages to install' && \ - rm /home/extractor/packages.txt) - -RUN [ -s /home/extractor/requirements.txt ] && \ - (echo "Install python modules" && \ - python3 -m pip install -U --no-cache-dir pip && \ - python3 -m pip install --no-cache-dir setuptools && \ - python3 -m pip install --no-cache-dir -r /home/extractor/requirements.txt && \ - rm /home/extractor/requirements.txt) || \ - (echo "No python modules to install" && \ - rm /home/extractor/requirements.txt) - -USER extractor - -COPY configuration.py transformer.py /home/extractor/ +# SciF Entrypoint +ENTRYPOINT ["scif"] \ No newline at end of file diff --git a/entrypoint.py b/entrypoint.py new file mode 100755 index 0000000..2db27cb --- /dev/null +++ b/entrypoint.py @@ -0,0 +1,409 @@ +#!/usr/bin/env python3 +"""Base entry point for Agriculture Pipeline transformer +""" + +import argparse +import os +import json +import logging +from typing import Optional +import yaml + +import transformer_class + +# From derived images +import configuration +import transformer + +class __internal__(): + """Class for functions intended for internal use only for this file + """ + def __init__(self): + """Performs initialization of class instance + """ + + @staticmethod + def handle_error(code: int, message: str) -> dict: + """Handles logging and return values when an error occurs. Implies processing + will stop. + Arguments: + code: return code related to the error + message: the message string of the error + Return: + Returns a dict with the code and message + """ + if code is None: + logging.warning("An error has occurred without a return code specified, setting default return code") + code = -1 + if not message: + logging.warning("An error has occurred without a message, setting default message") + message = "An error has occurred with error code (%s)" % str(code) + + logging.error(message) + logging.error("Stopping processing") + + result = {'error': message, 'code': code} + + return result + + @staticmethod + def load_metadata(metadata_path: str) -> dict: + """Loads the metadata from the specified path + Arguments: + metadata_path: path to the metadata file + Return: + Returns a dict containing the loaded metadata. If an error occurs, the dict + won't contain metadata but will contain an error message under an 'error' key. + """ + try: + if os.path.splitext(metadata_path)[1] in ('.yml', '.yaml'): + load_func = yaml.safe_load + else: + load_func = json.load + with open(metadata_path, 'r') as in_file: + md_load = load_func(in_file) + if md_load is not None: + md_return = {'metadata': md_load} + else: + msg = 'Invalid JSON/YAML specified in metadata file "%s"' % metadata_path + logging.error(msg) + md_return = {'error': msg} + except Exception as ex: + msg = "Unable to load metadata file '%s'" % metadata_path + logging.error(msg) + logging.error('Exception caught: %s', str(ex)) + if logging.getLogger().level == logging.DEBUG: + logging.exception(msg) + md_return = {'error': msg} + + return md_return + + @staticmethod + def check_params_result_error(transformer_params: dict) -> Optional[dict]: + """Checks the transformer parameter results for an error + Arguments: + transformer_params: the dictionary to check for errors + Return: + An error dict if errors were found and None if not + Notes: + See handle_error() function + """ + if 'code' in transformer_params: + if 'error' in transformer_params: + error = transformer_params['error'] + else: + error = "Error returned from get_transformer_params with code: %s" % transformer_params['code'] + return __internal__.handle_error(-104, error) + + return None + + @staticmethod + def check_retrieve_results_error(transformer_retrieve: tuple) -> Optional[dict]: + """Checks the results of the transformer_class retrieving files + Arguments: + transformer_retrieve: the results of the retrieve + Return: + An error dict if errors were found and None if not + Notes: + See handle_error() function + """ + if not transformer_retrieve: + return None + + code = 0 + message = None + retrieve_len = len(transformer_retrieve) + if retrieve_len > 0: + code = transformer_retrieve[0] + if retrieve_len > 1: + message = transformer_retrieve[1] + else: + message = "Retrieving files returned a code of %s" % str(code) + + # Check for an error code + if code < 0: + return __internal__.handle_error(code, message) + + # Log the message if we get one returned to us + if retrieve_len > 1: + logging.info(transformer_retrieve[1]) + + return None + + @staticmethod + def check_metadata_needed() -> bool: + """Checks if metadata is required + Return: + Returns True if metadata is required (the default is that it's required), or False if not + """ + # Disable the following check since it's not a valid test here (METADATA_NEEDED is an optional variable) + # pylint: disable=no-member + + # If we have a variable defined, check the many ways of determining False + if hasattr(configuration, "METADATA_NEEDED"): + if not configuration.METADATA_NEEDED: + return False + if isinstance(configuration.METADATA_NEEDED, str): + if configuration.METADATA_NEEDED.lower().strip() == 'false': + return False + return True + + @staticmethod + def load_metadata_files(metadata_files: list) -> dict: + """Loads the specified metadata files + Arguments: + metadata_files: list of metadata files to load + Returns: + Returns a dict containing the loaded metadata as an array. If an error occurs, the dict + won't contain metadata but will contain an error message under an 'error' key. + """ + metadata = [] + result = {'metadata': metadata} + for metadata_file in metadata_files: + if not os.path.exists(metadata_file): + result = __internal__.handle_error(-2, "Unable to access metadata file '%s'" % metadata_file) + break + logging.info("Loading metadata from file: '%s'", metadata_file) + md_loaded = __internal__.load_metadata(metadata_file) + if 'metadata' in md_loaded: + metadata.append(md_loaded['metadata']) + else: + result = __internal__.handle_error(-3, md_loaded['error']) + break + + return result + + @staticmethod + def parse_continue_result(result) -> tuple: + """Parses the result of calling transformer.check_continue and returns + the code and/or message + Arguments: + result: the result from calling transformer.check_continue + Return: + A tuple containing the result code and result message. One or both of these + values in the tuple may be None + Notes: + A string parameter will always return a result code of None and message of None indicating + the caller needs to decide what to do. + An integer parameter will cause the result message value of None, the caller needs to decide + what an appropriate message is. + A parameter that's iterable with a length > 0 will have the first value as the result code and the + second value as the result message. No checks are made for type conformity. + If the parameter is something other than the above, an exception will most likely be thrown. + """ + result_code = None + result_message = None + + if isinstance(result, int): + result_code = result + elif not isinstance(result, str): + result_len = len(result) + if result_len > 0: + result_code = result[0] + if result_len > 1: + result_message = result[1] + + return (result_code, result_message) + + @staticmethod + def handle_check_continue(transformer_instance: transformer_class.Transformer, transformer_params: dict) -> dict: + """Handles calling the transformer.check_continue function + Arguments: + transformer_instance: instance of Transformer class + transformer_params: dictionary of parameters to pass to transform module functions + Return: + Returns the result of checking to continue operation + """ + result = {} + + if hasattr(transformer, 'check_continue'): + check_result = transformer.check_continue(transformer_instance, **transformer_params) + result_code, result_message = __internal__.parse_continue_result(check_result) + + if result_code: + result['code'] = result_code + if result_message: + result['message'] = result_message + else: + logging.debug("transformer module doesn't have a function named 'check_continue'") + + return result + + @staticmethod + def handle_retrieve_files(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) ->\ + Optional[dict]: + """Handles calling the transformer class to retrieve files + Arguments: + transformer_instance: the current transformer environment + args: the command line arguments + metadata: the loaded metadata + Return: + A dict containing error information if a problem occurs and None if no problems are found. + Note: + A side effect of this function is a information message logged if the transformer class instance does not have + a 'retrieve_files' function declared. + """ + if hasattr(transformer_instance, 'retrieve_files'): + transformer_retrieve = transformer_instance.retrieve_files(args, metadata) + retrieve_results = __internal__.check_retrieve_results_error(transformer_retrieve) + if retrieve_results: + return retrieve_results + else: + logging.info("Transformer class doesn't have function named 'retrieve_files'") + + return None + + @staticmethod + def perform_processing(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) -> dict: + """Makes the calls to perform the processing + Arguments: + transformer_instance: instance of transformer class + args: the command line arguments + metadata: the loaded metadata + Return: + Returns a dict containing the result of processing + """ + result = {} + + # Get the various types of parameters from the transformer instance + if hasattr(transformer_instance, 'get_transformer_params'): + transformer_params = transformer_instance.get_transformer_params(args, metadata) + if not isinstance(transformer_params, dict): + return __internal__.handle_error(-101, + "Invalid return from getting transformer parameters from transformer class instance") + + params_result = __internal__.check_params_result_error(transformer_params) + if params_result: + return params_result + else: + logging.info("Transformer class instance does not have get_transformer_params method") + transformer_params = {} + + # First check if the transformer thinks everything is in place + if hasattr(transformer, 'check_continue'): + result = __internal__.handle_check_continue(transformer_instance, transformer_params) + if 'code' in result and result['code'] < 0 and 'error' not in result: + result['error'] = "Unknown error returned from check_continue call" + else: + logging.info("Transformer module doesn't have a function named 'check_continue'") + + # Retrieve additional files if indicated by return code from the check + if 'error' not in result and 'code' in result and result['code'] == 0: + result = __internal__.handle_retrieve_files(transformer_instance, args, metadata) + + # Next make the call to perform the processing + if 'error' not in result: + if hasattr(transformer, 'perform_process'): + result = transformer.perform_process(transformer_instance, **transformer_params) + else: + logging.debug("Transformer module is missing function named 'perform_process'") + return __internal__.handle_error(-102, "Transformer perform_process interface is not available " + + "for processing data") + + return result + + @staticmethod + def handle_result(result: dict, result_types: str = None, result_file_path: str = None) -> dict: + """Handles the results of processing as dictated by the arguments passed in. + Arguments: + result: the dictionary of result information + result_types: optional, comma separated string containing one or more of: all, file, print + result_file_path: optional, location to place result file + Return: + Returns the result parameter + Notes: + If result_types is None then no actions are taken. If 'file' or 'all' is specified + in result_types and result_file_path is None or empty, writing to a file is skipped + """ + if not result_types is None: + type_parts = [one_type.strip() for one_type in result_types.split(',')] + if 'print' in type_parts or 'all' in type_parts: + print(json.dumps(result, indent=2)) + if 'file' in type_parts or 'all' in type_parts: + if result_file_path: + os.makedirs(os.path.dirname(result_file_path), exist_ok=True) + with open(result_file_path, 'w') as out_file: + json.dump(result, out_file, indent=2) + else: + logging.warning("Writing result to a file was requested but a file path wasn't provided.") + logging.warning(" Skipping writing to a file.") + + return result + +def add_parameters(parser: argparse.ArgumentParser, transformer_instance) -> None: + """Function to prepare and execute work unit + Arguments: + parser: an instance of argparse.ArgumentParser + """ + parser.add_argument('--debug', '-d', action='store_const', + default=logging.WARN, const=logging.DEBUG, + help='enable debug logging (default=WARN)') + + parser.add_argument('--info', '-i', action='store_const', + default=logging.WARN, const=logging.INFO, + help='enable info logging (default=WARN)') + + parser.add_argument('--result', nargs='?', default='all', + help='Direct the result of a run to one or more of (all is default): "all,file,print"') + + parser.add_argument('--metadata', type=str, action='append', help='The path to the source metadata') + + parser.add_argument('--working_space', type=str, help='the folder to use use as a workspace and ' + + 'for storing results') + + # Let the transformer class add parameters + if hasattr(transformer_instance, 'add_parameters'): + transformer_instance.add_parameters(parser) + + # Check if the transformer has a function defined to extend command line arguments + if hasattr(transformer, 'add_parameters'): + transformer.add_parameters(parser) + + # Assume the rest of the arguments are the files + parser.add_argument('file_list', nargs=argparse.REMAINDER, help='additional files for transformer') + +def do_work(parser: argparse.ArgumentParser, **kwargs) -> dict: + """Function to prepare and execute work unit + Arguments: + parser: an instance of argparse.ArgumentParser + kwargs: keyword args + """ + result = {} + + # Create an instance of the transformer + transformer_instance = transformer_class.Transformer(**kwargs) + if not transformer_instance: + result = __internal__.handle_error(-100, "Unable to create transformer class instance for processing") + return __internal__.handle_result(result, None, None) + + add_parameters(parser, transformer_instance) + args = parser.parse_args() + + # start logging system + logging.getLogger().setLevel(args.debug if args.debug == logging.DEBUG else args.info) + + # Check that we have mandatory metadata + if not args.metadata and __internal__.check_metadata_needed(): + result = __internal__.handle_error(-1, "No metadata paths were specified.") + else: + md_results = __internal__.load_metadata_files(args.metadata) + if 'metadata' in md_results: + result = __internal__.perform_processing(transformer_instance, args, md_results['metadata']) + else: + result = __internal__.handle_error(-3, md_results['error']) + + if args.working_space: + result_path = os.path.join(args.working_space, 'result.json') + else: + result_path = None + + __internal__.handle_result(result, args.result, result_path) + return result + +if __name__ == "__main__": + try: + PARSER = argparse.ArgumentParser(description=configuration.TRANSFORMER_DESCRIPTION) + do_work(PARSER) + except Exception as ex: + logging.error("Top level exception handler caught an exception: %s", str(ex)) + raise diff --git a/recipe.scif b/recipe.scif new file mode 100644 index 0000000..d9639b5 --- /dev/null +++ b/recipe.scif @@ -0,0 +1,7 @@ +%appinstall soilmask + mv src/entrypoint.py bin/entrypoint.py +%apprun soilmask + exec entrypoint.py +%apphelp soilmask + This app provides an entrypoint to the soilmask tool + docker run agdrone/transformer-soilmask:3.0 run soilmask \ No newline at end of file diff --git a/transformer_class.py b/transformer_class.py new file mode 100644 index 0000000..a4937e7 --- /dev/null +++ b/transformer_class.py @@ -0,0 +1,261 @@ +"""Class instance for Transformer +""" + +import os +import argparse +import datetime +import logging + +from terrautils.imagefile import get_epsg as tr_get_epsg, \ + image_get_geobounds as tr_image_get_geobounds +import terrautils.lemnatec +import piexif + +import configuration + +terrautils.lemnatec.SENSOR_METADATA_CACHE = os.path.dirname(os.path.realpath(__file__)) + +# EXIF tags to look for +EXIF_ORIGIN_TIMESTAMP = 36867 # Capture timestamp +EXIF_TIMESTAMP_OFFSET = 36881 # Timestamp UTC offset (general) +EXIF_ORIGIN_TIMESTAMP_OFFSET = 36881 # Capture timestamp UTC offset + + +class __internal__(): + """Class containing functions for this file only + """ + def __init__(self): + """Perform class level initialization + """ + + @staticmethod + def exif_tags_to_timestamp(exif_tags): + """Looks up the origin timestamp and a timestamp offset in the exit tags and returns + a datetime object + Args: + exif_tags(dict): The exif tags to search for timestamp information + Return: + Returns the origin timestamp when found. The return timestamp is adjusted for UTF if + an offset is found. None is returned if a valid timestamp isn't found. + """ + cur_stamp, cur_offset = (None, None) + + def convert_and_clean_tag(value): + """Internal helper function for handling EXIF tag values. Tests for an empty string after + stripping colons, '+', '-', and whitespace [the spec is unclear if a +/- is needed when + the timestamp offset is unknown (and spaces are used)]. + Args: + value(bytes or str): The tag value + Return: + Returns the cleaned up, and converted from bytes, string. Or None if the value is empty + after stripping above characters and whitespace. + """ + if not value: + return None + + # Convert bytes to string + if isinstance(value, bytes): + value = value.decode('UTF-8').strip() + else: + value = value.strip() + + # Check for an empty string after stripping colons + if value: + if not value.replace(":", "").replace("+:", "").replace("-", "").strip(): + value = None + + return None if not value else value + + # Process the EXIF data + if EXIF_ORIGIN_TIMESTAMP in exif_tags: + cur_stamp = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP]) + if not cur_stamp: + return None + + if EXIF_ORIGIN_TIMESTAMP_OFFSET in exif_tags: + cur_offset = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP_OFFSET]) + if not cur_offset and EXIF_TIMESTAMP_OFFSET in exif_tags: + cur_offset = convert_and_clean_tag(exif_tags[EXIF_TIMESTAMP_OFFSET]) + + # Format the string to a timestamp and return the result + try: + if not cur_offset: + cur_ts = datetime.datetime.fromisoformat(cur_stamp) + else: + cur_offset = cur_offset.replace(":", "") + cur_ts = datetime.datetime.fromisoformat(cur_stamp + cur_offset) + except Exception as ex: + cur_ts = None + logging.debug("Exception caught converting EXIF tag to timestamp: %s", str(ex)) + + return cur_ts + + @staticmethod + def get_first_timestamp(file_path: str, timestamp: str = None) -> str: + """Looks for a timestamp in the specified file and returns + the earliest timestamp (when compared to the timestamp parameter) + Arguments: + file_path: the path to the file to check + timestamp: the timestamp to compare against (when specified) + Return: + The earliest found timestamp + """ + first_stamp = datetime.datetime.fromisoformat(timestamp) if timestamp else None + try: + tags_dict = piexif.load(file_path) + if tags_dict and "Exif" in tags_dict: + cur_stamp = __internal__.exif_tags_to_timestamp(tags_dict["Exif"]) + if cur_stamp: + first_stamp = cur_stamp if first_stamp is None or cur_stamp < first_stamp else first_stamp + except Exception as ex: + logging.debug("Exception caught getting timestamp from file: %s", file_path) + logging.debug(" %s", str(ex)) + + if first_stamp: + return first_stamp.isoformat() + + return timestamp + + +class Transformer(): + """Generic class for supporting transformers + """ + + def __init__(self, **kwargs): + """Performs initialization of class instance + Arguments: + kwargs: additional parameters passed in to Transformer + """ + # pylint: disable=unused-argument + self.sensor = None + self.args = None + + @property + def default_epsg(self) -> int: + """Returns the current working EPSG code + """ + return 4326 + + @property + def supported_image_file_exts(self): + """Returns the list of supported image file extension strings (in lower case) + """ + return ['tif', 'tiff', 'jpg'] + + def get_image_file_epsg(self, source_path: str) -> str: + """Returns the EPSG of the georeferenced image file + Arguments: + source_path: the path to the image to load the EPSG code from + Return: + Returns the EPSG code loaded from the file. None is returned if there is a problem or the file + doesn't have an EPSG code + """ + # pylint: disable=no-self-use + return tr_get_epsg(source_path) + + def get_image_file_geobounds(self, source_path: str) -> list: + """Uses gdal functionality to retrieve rectilinear boundaries from the file + Args: + source_path(str): path of the file to get the boundaries from + Returns: + The upper-left and calculated lower-right boundaries of the image in a list upon success. + The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan + is returned if the boundaries can't be determined + """ + # pylint: disable=no-self-use + return tr_image_get_geobounds(source_path) + + def generate_transformer_md(self) -> dict: + """Generates metadata about this transformer + Returns: + Returns the transformer metadata + """ + # pylint: disable=no-self-use + return { + 'version': configuration.TRANSFORMER_VERSION, + 'name': configuration.TRANSFORMER_NAME, + 'author': configuration.AUTHOR_NAME, + 'description': configuration.TRANSFORMER_DESCRIPTION, + 'repository': {'repUrl': configuration.REPOSITORY} + } + + def add_parameters(self, parser: argparse.ArgumentParser) -> None: + """Adds processing parameters to existing parameters + Arguments: + parser: instance of argparse + """ + # pylint: disable=no-self-use + parser.epilog = configuration.TRANSFORMER_NAME + ' version ' + configuration.TRANSFORMER_VERSION + \ + ' author ' + configuration.AUTHOR_NAME + ' ' + configuration.AUTHOR_EMAIL + + def get_transformer_params(self, args: argparse.Namespace, metadata: list) -> dict: + """Returns a parameter list for processing data + Arguments: + args: result of calling argparse.parse_args + metadata: the loaded metadata + """ + # Disabling this warning to keep code readable + # pylint: disable=too-many-branches + self.args = args + + timestamp, season_name, experiment_name = None, None, None + parsed_metadata = [] + transformer_md = [] + + # Loop through the metadata + for one_metadata in metadata: + # Determine if we're using JSONLD + if 'content' in one_metadata: + parse_md = one_metadata['content'] + else: + parse_md = one_metadata + # Check for legacy 'pipeline' key + if 'pipeline' in parse_md: + parse_md = parse_md['pipeline'] + parsed_metadata.append(parse_md) + + # Get the season, experiment, etc information + if 'observationTimeStamp' in parse_md: + timestamp = parse_md['observationTimeStamp'] + if 'season' in parse_md: + season_name = parse_md['season'] + if 'studyName' in parse_md: + experiment_name = parse_md['studyName'] + + # Check for transformer specific metadata + if configuration.TRANSFORMER_NAME in parse_md: + if isinstance(parse_md[configuration.TRANSFORMER_NAME], list): + transformer_md.extend(parse_md[configuration.TRANSFORMER_NAME]) + else: + transformer_md.append(parse_md[configuration.TRANSFORMER_NAME]) + # Get the list of files, if there are some and find the earliest timestamp if a timestamp + # hasn't been specified yet + file_list = [] + working_timestamp = timestamp + if args.file_list: + for one_file in args.file_list: + # Filter out arguments that are obviously not files + if not one_file.startswith('-'): + file_list.append(one_file) + # Only bother to get a timestamp if we don't have one specified + if timestamp is None: + working_timestamp = __internal__.get_first_timestamp(one_file, working_timestamp) + if timestamp is None and working_timestamp is not None: + timestamp = working_timestamp + + # Prepare our parameters + check_md = {'timestamp': timestamp, + 'season': season_name, + 'experiment': experiment_name, + 'container_name': None, + 'target_container_name': None, + 'trigger_name': None, + 'context_md': None, + 'working_folder': args.working_space, + 'list_files': lambda: file_list + } + + return {'check_md': check_md, + 'transformer_md': transformer_md, + 'full_md': parsed_metadata + } From b2df7d78814c2f1785048e987b70f0e1787975c3 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Tue, 21 Apr 2020 17:41:40 -0700 Subject: [PATCH 09/42] WIP: SCIF recipe for soilmask transformer Using conda environment. --- .gitignore | 3 +- Dockerfile | 8 +++++ package-list.txt | 87 ++++++++++++++++++++++++++++++++++++++++++++++++ recipe.scif | 10 +++++- 4 files changed, 106 insertions(+), 2 deletions(-) create mode 100644 package-list.txt diff --git a/.gitignore b/.gitignore index e2aeb1c..2030de3 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ .idea/* *.pyc -test \ No newline at end of file +test +.venv \ No newline at end of file diff --git a/Dockerfile b/Dockerfile index 44a4baf..c16071d 100644 --- a/Dockerfile +++ b/Dockerfile @@ -3,10 +3,18 @@ FROM agdrone/transformer-opendronemap:3.0 # Env variables ENV DEBIAN_FRONTEND noninteractive +RUN apt-get update -y \ + && apt-get install --no-install-recommends -y \ + wget +RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \ + && bash miniconda.sh -b +RUN ~/miniconda3/bin/conda update -n base -c defaults conda COPY transformer_class.py configuration.py entrypoint.py /scif/apps/soilmask/src/ COPY transformer.py /scif/apps/soilmask/src/ +COPY package-list.txt /scif/apps/soilmask/src/ # Install the filesystem from the recipe COPY *.scif / + RUN scif install /recipe.scif # Cleanup APT diff --git a/package-list.txt b/package-list.txt new file mode 100644 index 0000000..8bcca8b --- /dev/null +++ b/package-list.txt @@ -0,0 +1,87 @@ +# This file may be used to create an environment using: +# $ conda create --name --file +# platform: linux-64 +_libgcc_mutex=0.1=main +blas=1.0=mkl +bzip2=1.0.8=h7b6447c_0 +ca-certificates=2020.1.1=0 +cairo=1.14.12=h8948797_3 +certifi=2020.4.5.1=py37_0 +cloudpickle=1.3.0=py_0 +cycler=0.10.0=py37_0 +cytoolz=0.10.1=py37h7b6447c_0 +dask-core=2.14.0=py_0 +dbus=1.13.12=h746ee38_0 +decorator=4.4.2=py_0 +expat=2.2.6=he6710b0_0 +ffmpeg=4.0=hcdf2ecd_0 +fontconfig=2.13.0=h9420a91_0 +freeglut=3.0.0=hf484d3e_5 +freetype=2.9.1=h8a8886c_1 +glib=2.63.1=h5a9c865_0 +graphite2=1.3.13=h23475e2_0 +gst-plugins-base=1.14.0=hbbd80ab_1 +gstreamer=1.14.0=hb453b48_1 +harfbuzz=1.8.8=hffaf4a1_0 +hdf5=1.10.2=hba1933b_1 +icu=58.2=h9c2bf20_1 +imageio=2.8.0=py_0 +intel-openmp=2020.0=166 +jasper=2.0.14=h07fcdf6_1 +jpeg=9b=h024ee3a_2 +kiwisolver=1.1.0=py37he6710b0_0 +ld_impl_linux-64=2.33.1=h53a641e_7 +libedit=3.1.20181209=hc058e9b_0 +libffi=3.2.1=hd88cf55_4 +libgcc-ng=9.1.0=hdf63c60_0 +libgfortran-ng=7.3.0=hdf63c60_0 +libglu=9.0.0=hf484d3e_1 +libopencv=3.4.2=hb342d67_1 +libopus=1.3.1=h7b6447c_0 +libpng=1.6.37=hbc83047_0 +libstdcxx-ng=9.1.0=hdf63c60_0 +libtiff=4.1.0=h2733197_0 +libuuid=1.0.3=h1bed415_2 +libvpx=1.7.0=h439df22_0 +libxcb=1.13=h1bed415_1 +libxml2=2.9.9=hea5a465_1 +matplotlib=3.1.3=py37_0 +matplotlib-base=3.1.3=py37hef1b27d_0 +mkl=2020.0=166 +mkl-service=2.3.0=py37he904b0f_0 +mkl_fft=1.0.15=py37ha843d7b_0 +mkl_random=1.1.0=py37hd6b4f25_0 +ncurses=6.2=he6710b0_0 +networkx=2.4=py_0 +numpy=1.18.1=py37h4f9e942_0 +numpy-base=1.18.1=py37hde5b4d6_1 +olefile=0.46=py37_0 +opencv=3.4.2=py37h6fd60c2_1 +openssl=1.1.1g=h7b6447c_0 +pcre=8.43=he6710b0_0 +pillow=7.0.0=py37hb39fc2d_0 +pip=20.0.2=py37_1 +pixman=0.38.0=h7b6447c_0 +py-opencv=3.4.2=py37hb342d67_1 +pyparsing=2.4.6=py_0 +pyqt=5.9.2=py37h05f1152_2 +python=3.7.7=hcf32534_0_cpython +python-dateutil=2.8.1=py_0 +pywavelets=1.1.1=py37h7b6447c_0 +pyyaml=5.3.1=py37h7b6447c_0 +qt=5.9.7=h5867ecd_1 +readline=8.0=h7b6447c_0 +scikit-image=0.16.2=py37h0573a6f_0 +scipy=1.4.1=py37h0b6359f_0 +setuptools=46.1.3=py37_0 +sip=4.19.8=py37hf484d3e_0 +six=1.14.0=py37_0 +sqlite=3.31.1=h62c20be_1 +tk=8.6.8=hbc83047_0 +toolz=0.10.0=py_0 +tornado=6.0.4=py37h7b6447c_1 +wheel=0.34.2=py37_0 +xz=5.2.5=h7b6447c_0 +yaml=0.1.7=had09818_2 +zlib=1.2.11=h7b6447c_3 +zstd=1.3.7=h0b5b093_0 \ No newline at end of file diff --git a/recipe.scif b/recipe.scif index d9639b5..0905ea5 100644 --- a/recipe.scif +++ b/recipe.scif @@ -1,5 +1,13 @@ %appinstall soilmask - mv src/entrypoint.py bin/entrypoint.py + apt-get update -y + apt-get install --no-install-recommends -y libsm6 \ + libxext6 \ + libxrender1 \ + libglib2.0-0 + ~/miniconda3/bin/conda create --prefix "${PWD}" --yes --file src/package-list.txt + +%appenv soilmask + PATH=~/miniconda3/bin:$PATH %apprun soilmask exec entrypoint.py %apphelp soilmask From bddc320d60a0d3cf981b77dc9f1275f5596d0ced Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 23 Apr 2020 17:15:14 -0700 Subject: [PATCH 10/42] Working SCIF recipe for soilmask transformer. --- Dockerfile | 2 +- environment.yml | 170 +++++++++++++++++++++++++++++++++++++++++++++++ package-list.txt | 87 ------------------------ recipe.scif | 16 ++++- 4 files changed, 185 insertions(+), 90 deletions(-) create mode 100644 environment.yml delete mode 100644 package-list.txt diff --git a/Dockerfile b/Dockerfile index c16071d..5449b58 100644 --- a/Dockerfile +++ b/Dockerfile @@ -11,7 +11,7 @@ RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh - RUN ~/miniconda3/bin/conda update -n base -c defaults conda COPY transformer_class.py configuration.py entrypoint.py /scif/apps/soilmask/src/ COPY transformer.py /scif/apps/soilmask/src/ -COPY package-list.txt /scif/apps/soilmask/src/ +COPY environment.yml /scif/apps/soilmask/src/ # Install the filesystem from the recipe COPY *.scif / diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..bd05246 --- /dev/null +++ b/environment.yml @@ -0,0 +1,170 @@ +name: null +channels: + - conda-forge + - defaults +dependencies: + - _libgcc_mutex=0.1=conda_forge + - _openmp_mutex=4.5=1_llvm + - boost-cpp=1.72.0=h8e57a91_0 + - brotlipy=0.7.0=py38h1e0a361_1000 + - bzip2=1.0.8=h516909a_2 + - ca-certificates=2020.4.5.1=hecc5488_0 + - cairo=1.16.0=hcf35c78_1003 + - certifi=2020.4.5.1=py38h32f6830_0 + - cffi=1.14.0=py38hd463f26_0 + - cfitsio=3.470=hb60a0a2_2 + - cftime=1.1.1.2=py38h8790de6_0 + - cfunits=3.1.1=py_0 + - chardet=3.0.4=py38h32f6830_1006 + - cloudpickle=1.3.0=py_0 + - cryptography=2.8=py38h766eaa4_2 + - curl=7.69.1=h33f0ec9_0 + - cycler=0.10.0=py_2 + - cytoolz=0.10.1=py38h516909a_0 + - dask-core=2.14.0=py_0 + - dbus=1.13.6=he372182_0 + - decorator=4.4.2=py_0 + - expat=2.2.9=he1b5a44_2 + - ffmpeg=4.2=h167e202_0 + - fontconfig=2.13.1=h86ecdb6_1001 + - freetype=2.10.1=he06d7ca_0 + - freexl=1.0.5=h14c3975_1002 + - gdal=3.0.4=py38h172510d_4 + - geos=3.8.1=he1b5a44_0 + - geotiff=1.5.1=h05acad5_10 + - gettext=0.19.8.1=hc5be6a0_1002 + - giflib=5.2.1=h516909a_2 + - glib=2.64.2=h6f030ca_0 + - gmp=6.2.0=he1b5a44_2 + - gnutls=3.6.5=hd3a4fd2_1002 + - graphite2=1.3.13=he1b5a44_1001 + - gst-plugins-base=1.14.5=h0935bb2_2 + - gstreamer=1.14.5=h36ae1b5_2 + - harfbuzz=2.4.0=h9f30f68_3 + - hdf4=4.2.13=hf30be14_1003 + - hdf5=1.10.5=nompi_h3c11f04_1104 + - icu=64.2=he1b5a44_1 + - idna=2.9=py_1 + - imageio=2.8.0=py_0 + - influxdb=5.3.0=pyh9f0ad1d_0 + - jasper=1.900.1=h07fcdf6_1006 + - jpeg=9c=h14c3975_1001 + - json-c=0.13.1=h14c3975_1001 + - kealib=1.4.13=hec59c27_0 + - kiwisolver=1.2.0=py38hbf85e49_0 + - krb5=1.17.1=h2fd8d38_0 + - lame=3.100=h14c3975_1001 + - laspy=1.7.0=pyh5ca1d4c_0 + - lastools=20171231=hf484d3e_1000 + - laszip=3.4.3=he1b5a44_1 + - ld_impl_linux-64=2.34=h53a641e_0 + - libblas=3.8.0=16_openblas + - libcblas=3.8.0=16_openblas + - libclang=9.0.1=default_hde54327_0 + - libcurl=7.69.1=hf7181ac_0 + - libdap4=3.20.6=h1d1bd15_0 + - libedit=3.1.20170329=hf8c457e_1001 + - libffi=3.2.1=he1b5a44_1007 + - libgcc-ng=9.2.0=h24d8f2e_2 + - libgdal=3.0.4=h9e6407a_4 + - libgfortran-ng=7.3.0=hdf63c60_5 + - libiconv=1.15=h516909a_1006 + - libkml=1.3.0=hb574062_1011 + - liblapack=3.8.0=16_openblas + - liblapacke=3.8.0=16_openblas + - libllvm9=9.0.1=he513fc3_1 + - libnetcdf=4.7.4=nompi_h9f9fd6a_101 + - libopenblas=0.3.9=h5ec1e0e_0 + - libopencv=4.2.0=py38_5 + - libpng=1.6.37=hed695b0_1 + - libpq=12.2=h5513abc_1 + - libspatialite=4.3.0a=h2482549_1038 + - libssh2=1.8.2=h22169c7_2 + - libstdcxx-ng=9.2.0=hdf63c60_2 + - libtiff=4.1.0=hc3755c2_3 + - libuuid=2.32.1=h14c3975_1000 + - libwebp=1.0.2=h56121f0_5 + - libxcb=1.13=h14c3975_1002 + - libxkbcommon=0.10.0=he1b5a44_0 + - libxml2=2.9.10=hee79883_0 + - llvm-openmp=10.0.0=hc9558a2_0 + - lz4-c=1.8.3=he1b5a44_1001 + - matplotlib=3.2.1=0 + - matplotlib-base=3.2.1=py38h2af1d28_0 + - msgpack-python=1.0.0=py38hbf85e49_1 + - ncurses=6.1=hf484d3e_1002 + - netcdf4=1.5.3=nompi_py38heb6102f_103 + - nettle=3.4.1=h1bed415_1002 + - networkx=2.4=py_1 + - nspr=4.25=he1b5a44_0 + - nss=3.47=he751ad9_0 + - numpy=1.18.1=py38h8854b6b_1 + - olefile=0.46=py_0 + - opencv=4.2.0=py38_5 + - openh264=1.8.0=hdbcaa40_1000 + - openjpeg=2.3.1=h981e76c_3 + - openssl=1.1.1g=h516909a_0 + - pcre=8.44=he1b5a44_0 + - piexif=1.1.3=py_2 + - pika=1.1.0=py_0 + - pillow=7.1.1=py38h9776b28_0 + - pip=20.0.2=py_2 + - pixman=0.38.0=h516909a_1003 + - poppler=0.67.0=h14e79db_8 + - poppler-data=0.4.9=1 + - postgresql=12.2=h8573dbc_1 + - proj=7.0.0=h966b41f_3 + - pthread-stubs=0.4=h14c3975_1001 + - py-opencv=4.2.0=py38h23f93f0_5 + - pycparser=2.20=py_0 + - pyopenssl=19.1.0=py_1 + - pyparsing=2.4.7=pyh9f0ad1d_0 + - pyqt=5.12.3=py38hcca6a23_1 + - pysocks=1.7.1=py38h32f6830_1 + - python=3.8.2=he5300dc_6_cpython + - python-dateutil=2.8.1=py_0 + - python-logstash=0.4.6=py_0 + - python_abi=3.8=1_cp38 + - pytz=2019.3=py_0 + - pywavelets=1.1.1=py38h8790de6_1 + - pyyaml=5.3.1=py38h1e0a361_0 + - qt=5.12.5=hd8c4c69_1 + - readline=8.0=hf8c457e_0 + - requests=2.23.0=pyh8c360ce_2 + - requests-toolbelt=0.9.1=py_0 + - scikit-image=0.16.2=py38hb3f55d8_0 + - scipy=1.4.1=py38h18bccfc_3 + - setuptools=46.1.3=py38h32f6830_0 + - six=1.14.0=py_1 + - sqlite=3.30.1=hcee41ef_0 + - tbb=2018.0.5=h2d50403_0 + - tiledb=1.7.0=hcde45ca_2 + - tk=8.6.10=hed695b0_0 + - toolz=0.10.0=py_0 + - tornado=6.0.4=py38h1e0a361_1 + - tzcode=2019a=h516909a_1002 + - udunits2=2.2.27.6=h4e0c4b3_1001 + - urllib3=1.25.9=py_0 + - utm=0.5.0=py_0 + - wheel=0.34.2=py_1 + - x264=1!152.20180806=h14c3975_0 + - xerces-c=3.2.2=h8412b87_1004 + - xorg-kbproto=1.0.7=h14c3975_1002 + - xorg-libice=1.0.10=h516909a_0 + - xorg-libsm=1.2.3=h84519dc_1000 + - xorg-libx11=1.6.9=h516909a_0 + - xorg-libxau=1.0.9=h14c3975_0 + - xorg-libxdmcp=1.1.3=h516909a_0 + - xorg-libxext=1.3.4=h516909a_0 + - xorg-libxrender=0.9.10=h516909a_1002 + - xorg-renderproto=0.11.1=h14c3975_1002 + - xorg-xextproto=7.3.0=h14c3975_1002 + - xorg-xproto=7.0.31=h14c3975_1007 + - xz=5.2.5=h516909a_0 + - yaml=0.2.4=h516909a_0 + - zlib=1.2.11=h516909a_1006 + - zstd=1.4.4=h3b9ef0a_2 + - pip: + - pyqt5-sip==4.19.18 + - pyqtwebengine==5.12.1 +prefix: /scif/apps/soilmask/conda \ No newline at end of file diff --git a/package-list.txt b/package-list.txt deleted file mode 100644 index 8bcca8b..0000000 --- a/package-list.txt +++ /dev/null @@ -1,87 +0,0 @@ -# This file may be used to create an environment using: -# $ conda create --name --file -# platform: linux-64 -_libgcc_mutex=0.1=main -blas=1.0=mkl -bzip2=1.0.8=h7b6447c_0 -ca-certificates=2020.1.1=0 -cairo=1.14.12=h8948797_3 -certifi=2020.4.5.1=py37_0 -cloudpickle=1.3.0=py_0 -cycler=0.10.0=py37_0 -cytoolz=0.10.1=py37h7b6447c_0 -dask-core=2.14.0=py_0 -dbus=1.13.12=h746ee38_0 -decorator=4.4.2=py_0 -expat=2.2.6=he6710b0_0 -ffmpeg=4.0=hcdf2ecd_0 -fontconfig=2.13.0=h9420a91_0 -freeglut=3.0.0=hf484d3e_5 -freetype=2.9.1=h8a8886c_1 -glib=2.63.1=h5a9c865_0 -graphite2=1.3.13=h23475e2_0 -gst-plugins-base=1.14.0=hbbd80ab_1 -gstreamer=1.14.0=hb453b48_1 -harfbuzz=1.8.8=hffaf4a1_0 -hdf5=1.10.2=hba1933b_1 -icu=58.2=h9c2bf20_1 -imageio=2.8.0=py_0 -intel-openmp=2020.0=166 -jasper=2.0.14=h07fcdf6_1 -jpeg=9b=h024ee3a_2 -kiwisolver=1.1.0=py37he6710b0_0 -ld_impl_linux-64=2.33.1=h53a641e_7 -libedit=3.1.20181209=hc058e9b_0 -libffi=3.2.1=hd88cf55_4 -libgcc-ng=9.1.0=hdf63c60_0 -libgfortran-ng=7.3.0=hdf63c60_0 -libglu=9.0.0=hf484d3e_1 -libopencv=3.4.2=hb342d67_1 -libopus=1.3.1=h7b6447c_0 -libpng=1.6.37=hbc83047_0 -libstdcxx-ng=9.1.0=hdf63c60_0 -libtiff=4.1.0=h2733197_0 -libuuid=1.0.3=h1bed415_2 -libvpx=1.7.0=h439df22_0 -libxcb=1.13=h1bed415_1 -libxml2=2.9.9=hea5a465_1 -matplotlib=3.1.3=py37_0 -matplotlib-base=3.1.3=py37hef1b27d_0 -mkl=2020.0=166 -mkl-service=2.3.0=py37he904b0f_0 -mkl_fft=1.0.15=py37ha843d7b_0 -mkl_random=1.1.0=py37hd6b4f25_0 -ncurses=6.2=he6710b0_0 -networkx=2.4=py_0 -numpy=1.18.1=py37h4f9e942_0 -numpy-base=1.18.1=py37hde5b4d6_1 -olefile=0.46=py37_0 -opencv=3.4.2=py37h6fd60c2_1 -openssl=1.1.1g=h7b6447c_0 -pcre=8.43=he6710b0_0 -pillow=7.0.0=py37hb39fc2d_0 -pip=20.0.2=py37_1 -pixman=0.38.0=h7b6447c_0 -py-opencv=3.4.2=py37hb342d67_1 -pyparsing=2.4.6=py_0 -pyqt=5.9.2=py37h05f1152_2 -python=3.7.7=hcf32534_0_cpython -python-dateutil=2.8.1=py_0 -pywavelets=1.1.1=py37h7b6447c_0 -pyyaml=5.3.1=py37h7b6447c_0 -qt=5.9.7=h5867ecd_1 -readline=8.0=h7b6447c_0 -scikit-image=0.16.2=py37h0573a6f_0 -scipy=1.4.1=py37h0b6359f_0 -setuptools=46.1.3=py37_0 -sip=4.19.8=py37hf484d3e_0 -six=1.14.0=py37_0 -sqlite=3.31.1=h62c20be_1 -tk=8.6.8=hbc83047_0 -toolz=0.10.0=py_0 -tornado=6.0.4=py37h7b6447c_1 -wheel=0.34.2=py37_0 -xz=5.2.5=h7b6447c_0 -yaml=0.1.7=had09818_2 -zlib=1.2.11=h7b6447c_3 -zstd=1.3.7=h0b5b093_0 \ No newline at end of file diff --git a/recipe.scif b/recipe.scif index 0905ea5..5d4b375 100644 --- a/recipe.scif +++ b/recipe.scif @@ -4,12 +4,24 @@ libxext6 \ libxrender1 \ libglib2.0-0 - ~/miniconda3/bin/conda create --prefix "${PWD}" --yes --file src/package-list.txt + # Install conda packages: + ~/miniconda3/bin/conda env create --prefix "${PWD}/conda" -f src/environment.yml + + # To regenerate src/environment.yml: + # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge gdal scikit-image opencv PyYAML cfunits influxdb matplotlib netCDF4 numpy Pillow python-dateutil scipy utm python-logstash pika requests-toolbelt laspy piexif + # ~/miniconda3/bin/conda env export --prefix "${PWD}/conda" > src/environment.yml + + # Install terrautils: + mkdir tmp + git clone --branch master --single-branch --depth 1 https://github.com/terraref/terrautils.git tmp/terrautils + conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps pyclowder + conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps tmp/terrautils + rm -rf tmp/terrautils %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask - exec entrypoint.py + exec conda run --prefix "${SCIF_APPROOT}/conda" src/entrypoint.py %apphelp soilmask This app provides an entrypoint to the soilmask tool docker run agdrone/transformer-soilmask:3.0 run soilmask \ No newline at end of file From cf301eaa8795581e77490fffc8be01b4a5ae7513 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 23 Apr 2020 17:42:18 -0700 Subject: [PATCH 11/42] Fixed path to conda. --- recipe.scif | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/recipe.scif b/recipe.scif index 5d4b375..7656f6d 100644 --- a/recipe.scif +++ b/recipe.scif @@ -15,8 +15,8 @@ # Install terrautils: mkdir tmp git clone --branch master --single-branch --depth 1 https://github.com/terraref/terrautils.git tmp/terrautils - conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps pyclowder - conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps tmp/terrautils + ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps pyclowder + ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps tmp/terrautils rm -rf tmp/terrautils %appenv soilmask PATH=~/miniconda3/bin:$PATH From e8206331d41f159b727a9c26a682fcd4ae04d4e2 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Fri, 24 Apr 2020 15:34:51 -0700 Subject: [PATCH 12/42] Added git to the required packages for soilmask recipe. --- recipe.scif | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/recipe.scif b/recipe.scif index 7656f6d..e2f8dff 100644 --- a/recipe.scif +++ b/recipe.scif @@ -3,7 +3,8 @@ apt-get install --no-install-recommends -y libsm6 \ libxext6 \ libxrender1 \ - libglib2.0-0 + libglib2.0-0 \ + git # Install conda packages: ~/miniconda3/bin/conda env create --prefix "${PWD}/conda" -f src/environment.yml From d1017901bcf80fe867782c82734976221551771b Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Fri, 1 May 2020 17:25:23 -0700 Subject: [PATCH 13/42] Pass parameters to the entrypoint. --- recipe.scif | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipe.scif b/recipe.scif index e2f8dff..8204c09 100644 --- a/recipe.scif +++ b/recipe.scif @@ -22,7 +22,7 @@ %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask - exec conda run --prefix "${SCIF_APPROOT}/conda" src/entrypoint.py + exec conda run --prefix "${SCIF_APPROOT}/conda" src/entrypoint.py "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool docker run agdrone/transformer-soilmask:3.0 run soilmask \ No newline at end of file From e7b94b681d036bf0f39001755eb37750f20ef129 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Fri, 1 May 2020 17:44:45 -0700 Subject: [PATCH 14/42] Clean up APT. --- Dockerfile | 8 +++++--- recipe.scif | 2 ++ 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/Dockerfile b/Dockerfile index 5449b58..c9b1a9f 100644 --- a/Dockerfile +++ b/Dockerfile @@ -5,7 +5,9 @@ ENV DEBIAN_FRONTEND noninteractive RUN apt-get update -y \ && apt-get install --no-install-recommends -y \ - wget + wget \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \ && bash miniconda.sh -b RUN ~/miniconda3/bin/conda update -n base -c defaults conda @@ -18,8 +20,8 @@ COPY *.scif / RUN scif install /recipe.scif # Cleanup APT -#RUN apt-get clean \ -# && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* +RUN apt-get clean \ + && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # SciF Entrypoint ENTRYPOINT ["scif"] \ No newline at end of file diff --git a/recipe.scif b/recipe.scif index 8204c09..b2a1917 100644 --- a/recipe.scif +++ b/recipe.scif @@ -6,6 +6,8 @@ libglib2.0-0 \ git + apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* + # Install conda packages: ~/miniconda3/bin/conda env create --prefix "${PWD}/conda" -f src/environment.yml From f4d48ff8ee757fcb0aa6ed5dcb451e984646b929 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Tue, 5 May 2020 17:53:43 -0700 Subject: [PATCH 15/42] Simplified scif recipe to only install opencv and numpy. --- environment.yml | 98 +++++-------------------------------------------- recipe.scif | 19 +--------- 2 files changed, 11 insertions(+), 106 deletions(-) diff --git a/environment.yml b/environment.yml index bd05246..cf5ae2d 100644 --- a/environment.yml +++ b/environment.yml @@ -5,33 +5,15 @@ channels: dependencies: - _libgcc_mutex=0.1=conda_forge - _openmp_mutex=4.5=1_llvm - - boost-cpp=1.72.0=h8e57a91_0 - - brotlipy=0.7.0=py38h1e0a361_1000 - bzip2=1.0.8=h516909a_2 - ca-certificates=2020.4.5.1=hecc5488_0 - cairo=1.16.0=hcf35c78_1003 - certifi=2020.4.5.1=py38h32f6830_0 - - cffi=1.14.0=py38hd463f26_0 - - cfitsio=3.470=hb60a0a2_2 - - cftime=1.1.1.2=py38h8790de6_0 - - cfunits=3.1.1=py_0 - - chardet=3.0.4=py38h32f6830_1006 - - cloudpickle=1.3.0=py_0 - - cryptography=2.8=py38h766eaa4_2 - - curl=7.69.1=h33f0ec9_0 - - cycler=0.10.0=py_2 - - cytoolz=0.10.1=py38h516909a_0 - - dask-core=2.14.0=py_0 - dbus=1.13.6=he372182_0 - - decorator=4.4.2=py_0 - expat=2.2.9=he1b5a44_2 - ffmpeg=4.2=h167e202_0 - fontconfig=2.13.1=h86ecdb6_1001 - freetype=2.10.1=he06d7ca_0 - - freexl=1.0.5=h14c3975_1002 - - gdal=3.0.4=py38h172510d_4 - - geos=3.8.1=he1b5a44_0 - - geotiff=1.5.1=h05acad5_10 - gettext=0.19.8.1=hc5be6a0_1002 - giflib=5.2.1=h516909a_2 - glib=2.64.2=h6f030ca_0 @@ -41,45 +23,25 @@ dependencies: - gst-plugins-base=1.14.5=h0935bb2_2 - gstreamer=1.14.5=h36ae1b5_2 - harfbuzz=2.4.0=h9f30f68_3 - - hdf4=4.2.13=hf30be14_1003 - - hdf5=1.10.5=nompi_h3c11f04_1104 + - hdf5=1.10.6=nompi_h3c11f04_100 - icu=64.2=he1b5a44_1 - - idna=2.9=py_1 - - imageio=2.8.0=py_0 - - influxdb=5.3.0=pyh9f0ad1d_0 - jasper=1.900.1=h07fcdf6_1006 - jpeg=9c=h14c3975_1001 - - json-c=0.13.1=h14c3975_1001 - - kealib=1.4.13=hec59c27_0 - - kiwisolver=1.2.0=py38hbf85e49_0 - - krb5=1.17.1=h2fd8d38_0 - lame=3.100=h14c3975_1001 - - laspy=1.7.0=pyh5ca1d4c_0 - - lastools=20171231=hf484d3e_1000 - - laszip=3.4.3=he1b5a44_1 - ld_impl_linux-64=2.34=h53a641e_0 - libblas=3.8.0=16_openblas - libcblas=3.8.0=16_openblas - libclang=9.0.1=default_hde54327_0 - - libcurl=7.69.1=hf7181ac_0 - - libdap4=3.20.6=h1d1bd15_0 - - libedit=3.1.20170329=hf8c457e_1001 - libffi=3.2.1=he1b5a44_1007 - libgcc-ng=9.2.0=h24d8f2e_2 - - libgdal=3.0.4=h9e6407a_4 - libgfortran-ng=7.3.0=hdf63c60_5 - libiconv=1.15=h516909a_1006 - - libkml=1.3.0=hb574062_1011 - liblapack=3.8.0=16_openblas - liblapacke=3.8.0=16_openblas - libllvm9=9.0.1=he513fc3_1 - - libnetcdf=4.7.4=nompi_h9f9fd6a_101 - libopenblas=0.3.9=h5ec1e0e_0 - - libopencv=4.2.0=py38_5 + - libopencv=4.2.0=py38_6 - libpng=1.6.37=hed695b0_1 - - libpq=12.2=h5513abc_1 - - libspatialite=4.3.0a=h2482549_1038 - - libssh2=1.8.2=h22169c7_2 - libstdcxx-ng=9.2.0=hdf63c60_2 - libtiff=4.1.0=hc3755c2_3 - libuuid=2.32.1=h14c3975_1000 @@ -88,67 +50,29 @@ dependencies: - libxkbcommon=0.10.0=he1b5a44_0 - libxml2=2.9.10=hee79883_0 - llvm-openmp=10.0.0=hc9558a2_0 - - lz4-c=1.8.3=he1b5a44_1001 - - matplotlib=3.2.1=0 - - matplotlib-base=3.2.1=py38h2af1d28_0 - - msgpack-python=1.0.0=py38hbf85e49_1 + - lz4-c=1.9.2=he1b5a44_1 - ncurses=6.1=hf484d3e_1002 - - netcdf4=1.5.3=nompi_py38heb6102f_103 - nettle=3.4.1=h1bed415_1002 - - networkx=2.4=py_1 - nspr=4.25=he1b5a44_0 - nss=3.47=he751ad9_0 - - numpy=1.18.1=py38h8854b6b_1 - - olefile=0.46=py_0 - - opencv=4.2.0=py38_5 + - numpy=1.18.4=py38h8854b6b_0 + - opencv=4.2.0=py38_6 - openh264=1.8.0=hdbcaa40_1000 - - openjpeg=2.3.1=h981e76c_3 - openssl=1.1.1g=h516909a_0 - pcre=8.44=he1b5a44_0 - - piexif=1.1.3=py_2 - - pika=1.1.0=py_0 - - pillow=7.1.1=py38h9776b28_0 - - pip=20.0.2=py_2 + - pip=20.1=pyh9f0ad1d_0 - pixman=0.38.0=h516909a_1003 - - poppler=0.67.0=h14e79db_8 - - poppler-data=0.4.9=1 - - postgresql=12.2=h8573dbc_1 - - proj=7.0.0=h966b41f_3 - pthread-stubs=0.4=h14c3975_1001 - - py-opencv=4.2.0=py38h23f93f0_5 - - pycparser=2.20=py_0 - - pyopenssl=19.1.0=py_1 - - pyparsing=2.4.7=pyh9f0ad1d_0 - - pyqt=5.12.3=py38hcca6a23_1 - - pysocks=1.7.1=py38h32f6830_1 - - python=3.8.2=he5300dc_6_cpython - - python-dateutil=2.8.1=py_0 - - python-logstash=0.4.6=py_0 + - py-opencv=4.2.0=py38h23f93f0_6 + - python=3.8.2=he5300dc_7_cpython - python_abi=3.8=1_cp38 - - pytz=2019.3=py_0 - - pywavelets=1.1.1=py38h8790de6_1 - - pyyaml=5.3.1=py38h1e0a361_0 - qt=5.12.5=hd8c4c69_1 - readline=8.0=hf8c457e_0 - - requests=2.23.0=pyh8c360ce_2 - - requests-toolbelt=0.9.1=py_0 - - scikit-image=0.16.2=py38hb3f55d8_0 - - scipy=1.4.1=py38h18bccfc_3 - setuptools=46.1.3=py38h32f6830_0 - - six=1.14.0=py_1 - sqlite=3.30.1=hcee41ef_0 - - tbb=2018.0.5=h2d50403_0 - - tiledb=1.7.0=hcde45ca_2 - tk=8.6.10=hed695b0_0 - - toolz=0.10.0=py_0 - - tornado=6.0.4=py38h1e0a361_1 - - tzcode=2019a=h516909a_1002 - - udunits2=2.2.27.6=h4e0c4b3_1001 - - urllib3=1.25.9=py_0 - - utm=0.5.0=py_0 - wheel=0.34.2=py_1 - x264=1!152.20180806=h14c3975_0 - - xerces-c=3.2.2=h8412b87_1004 - xorg-kbproto=1.0.7=h14c3975_1002 - xorg-libice=1.0.10=h516909a_0 - xorg-libsm=1.2.3=h84519dc_1000 @@ -161,10 +85,6 @@ dependencies: - xorg-xextproto=7.3.0=h14c3975_1002 - xorg-xproto=7.0.31=h14c3975_1007 - xz=5.2.5=h516909a_0 - - yaml=0.2.4=h516909a_0 - zlib=1.2.11=h516909a_1006 - - zstd=1.4.4=h3b9ef0a_2 - - pip: - - pyqt5-sip==4.19.18 - - pyqtwebengine==5.12.1 + - zstd=1.4.4=h6597ccf_3 prefix: /scif/apps/soilmask/conda \ No newline at end of file diff --git a/recipe.scif b/recipe.scif index b2a1917..c32743d 100644 --- a/recipe.scif +++ b/recipe.scif @@ -1,30 +1,15 @@ %appinstall soilmask - apt-get update -y - apt-get install --no-install-recommends -y libsm6 \ - libxext6 \ - libxrender1 \ - libglib2.0-0 \ - git - - apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* - # Install conda packages: ~/miniconda3/bin/conda env create --prefix "${PWD}/conda" -f src/environment.yml # To regenerate src/environment.yml: - # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge gdal scikit-image opencv PyYAML cfunits influxdb matplotlib netCDF4 numpy Pillow python-dateutil scipy utm python-logstash pika requests-toolbelt laspy piexif + # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge opencv numpy # ~/miniconda3/bin/conda env export --prefix "${PWD}/conda" > src/environment.yml - # Install terrautils: - mkdir tmp - git clone --branch master --single-branch --depth 1 https://github.com/terraref/terrautils.git tmp/terrautils - ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps pyclowder - ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 -m pip install --no-deps tmp/terrautils - rm -rf tmp/terrautils %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask exec conda run --prefix "${SCIF_APPROOT}/conda" src/entrypoint.py "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool - docker run agdrone/transformer-soilmask:3.0 run soilmask \ No newline at end of file + docker run agpipeline/transformer-soilmask run soilmask \ No newline at end of file From 83ee1a6da7ee70cc49ffaac19d5def6faf7ad5c2 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Wed, 6 May 2020 18:28:54 -0700 Subject: [PATCH 16/42] First draft of bare soil mask. Still need tests. --- Dockerfile | 6 +- Dockerfile.template | 26 --- README.md | 46 +---- configuration.py | 29 --- entrypoint.py | 409 ------------------------------------- generate_docker.py | 69 ------- main.py | 27 +++ packages.txt | 4 - recipe.scif | 4 +- requirements.txt | 2 - soilmask.py | 45 ++++ transformer.py | 474 ------------------------------------------- transformer_class.py | 261 ------------------------ 13 files changed, 78 insertions(+), 1324 deletions(-) delete mode 100644 Dockerfile.template delete mode 100644 configuration.py delete mode 100755 entrypoint.py delete mode 100755 generate_docker.py create mode 100644 main.py delete mode 100644 packages.txt delete mode 100644 requirements.txt create mode 100644 soilmask.py delete mode 100644 transformer_class.py diff --git a/Dockerfile b/Dockerfile index c9b1a9f..20bb0e3 100644 --- a/Dockerfile +++ b/Dockerfile @@ -11,12 +11,10 @@ RUN apt-get update -y \ RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \ && bash miniconda.sh -b RUN ~/miniconda3/bin/conda update -n base -c defaults conda -COPY transformer_class.py configuration.py entrypoint.py /scif/apps/soilmask/src/ -COPY transformer.py /scif/apps/soilmask/src/ -COPY environment.yml /scif/apps/soilmask/src/ +COPY . /scif/apps/soilmask/src/ + # Install the filesystem from the recipe COPY *.scif / - RUN scif install /recipe.scif # Cleanup APT diff --git a/Dockerfile.template b/Dockerfile.template deleted file mode 100644 index b638123..0000000 --- a/Dockerfile.template +++ /dev/null @@ -1,26 +0,0 @@ -# Version 1.0 template-transformer-simple - -FROM base-image -LABEL maintainer="" - -COPY requirements.txt packages.txt /home/extractor/ - -USER root - -RUN [ -s /home/extractor/packages.txt ] && \ - (echo 'Installing packages' && \ - apt-get update && \ - cat /home/extractor/packages.txt | xargs apt-get install -y --no-install-recommends && \ - rm /home/extractor/packages.txt && \ - apt-get autoremove -y && \ - apt-get clean && \ - rm -rf /var/lib/apt/lists/*) || \ - (echo 'No packages to install' && \ - rm /home/extractor/packages.txt) - -RUN python3 -m pip install --no-cache-dir -r /home/extractor/requirements.txt && \ - rm /home/extractor/requirements.txt - -USER extractor - -COPY configuration.py transformer.py /home/extractor/ diff --git a/README.md b/README.md index b529174..d5ea169 100644 --- a/README.md +++ b/README.md @@ -1,47 +1,5 @@ # Transformer Soil Mask -Masks out the soil in images - -### Sample Docker Command line -Below is a sample command line that shows how the soil mask Docker image could be run. -An explanation of the command line options used follows. -Be sure to read up on the [docker run](https://docs.docker.com/engine/reference/run/) command line for more information. - -```docker run --rm --mount "src=/home/test,target=/mnt,type=bind" agpipeline/soilmask:2.0 --working_space "/mnt" --metadata "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_metadata_cleaned.json" "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif" ``` - -This example command line assumes the source files are located in the `/home/test` folder of the local machine. -The name of the image to run is `agpipeline/soilmask:2.0`. - -We are using the same folder for the source files and the output files. -By using multiple `--mount` options, the source and output files can be separated. - -**Docker commands** \ -Everything between 'docker' and the name of the image are docker commands. -- `run` indicates we want to run an image -- `--rm` automatically delete the image instance after it's run -- `--mount "src=/home/test,target=/mnt,type=bind"` mounts the `/home/test` folder to the `/mnt` folder of the running image - -We mount the `/home/test` folder to the running image to make files available to the software in the image. - -**Image's commands** \ -The command line parameters after the image name are passed to the software inside the image. -Note that the paths provided are relative to the running image (see the --mount option specified above). - -- `--working_space "/mnt"` specifies the folder to use as a workspace -- `--metadata "/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_metadata.cleaned.json"` is the name of the source metadata to be cleaned -- `"/mnt/08f445ef-b8f9-421a-acf1-8b8c206c1bb8_left.tif"` is the name of the image to mask - -## Transformer class dependencies -This transformer has the following requirements from the [Environmental](https://github.com/AgPipeline/AgPipeline.github.io/blob/transformers/transformers/transformers.md) Transformer class. +Masks out the soil in images -Expected method signatures and explanations: -- **get_image_file_epsg(file_name: str) -> str**: function returns the EPSG code from a georeferenced image file, or None -- **default_epsg -> str**: property returning the expected EPSG; compared against a file's EPSG code to determine if the resulting mask file needs to be converted to match the default EPSG -- **get_image_file_geobounds(file_name: str) -> list**: function returns the geographic boundaries of a georeferenced image file as a list ordered as [min_y, max_y, min_x, max_x] or a list of four numpy.nan values if the file is not georeferenced -- **generate_transformer_md() -> dict**: function returns a dictionary with the following minimum set of keys: - - `name`: the name of the transformer (the configuration.py file can be used for this) - - `version`: the version of the transformer (the configuration.py file can be used for this) - - `author`: the author of the transformer (the configuration.py file can be used for this) - - `description`: the description of the transformer (the configuration.py file can be used for this) - - `repository`: optional repository URI of transformer source code (the configuration.py file can be used for this) - \ No newline at end of file +## TODO \ No newline at end of file diff --git a/configuration.py b/configuration.py deleted file mode 100644 index ba4e38b..0000000 --- a/configuration.py +++ /dev/null @@ -1,29 +0,0 @@ -"""Contains transformer configuration information -""" - -# The version number of the transformer -TRANSFORMER_VERSION = '2.0' - -# The transformer description -TRANSFORMER_DESCRIPTION = 'Stereo RGB Image Enhancement & Masking' - -# Short name of the transformer -TRANSFORMER_NAME = 'terra.stereo-rgb.rgbmask' - -# The name of the author of the extractor -AUTHOR_NAME = 'Chris Schnaufer' - -# The email of the author of the extractor -AUTHOR_EMAIL = 'schnaufer@email.arizona.edu' - -# Reposity URI of where the source code lives -REPOSITORY = 'https://github.com/Chris-Schnaufer/rgbmask.git' - -# Contributors to this transformer -CONTRUBUTORS = ['Max Burnette', 'Zongyang Li', 'Todd Nicholson'] - -# The sensor associated with the transformer -TRANSFORMER_SENSOR = 'stereoTop' - -# The transformer type (eg: 'rgbmask', 'plotclipper') -TRANSFORMER_TYPE = 'rgb_mask' diff --git a/entrypoint.py b/entrypoint.py deleted file mode 100755 index 2db27cb..0000000 --- a/entrypoint.py +++ /dev/null @@ -1,409 +0,0 @@ -#!/usr/bin/env python3 -"""Base entry point for Agriculture Pipeline transformer -""" - -import argparse -import os -import json -import logging -from typing import Optional -import yaml - -import transformer_class - -# From derived images -import configuration -import transformer - -class __internal__(): - """Class for functions intended for internal use only for this file - """ - def __init__(self): - """Performs initialization of class instance - """ - - @staticmethod - def handle_error(code: int, message: str) -> dict: - """Handles logging and return values when an error occurs. Implies processing - will stop. - Arguments: - code: return code related to the error - message: the message string of the error - Return: - Returns a dict with the code and message - """ - if code is None: - logging.warning("An error has occurred without a return code specified, setting default return code") - code = -1 - if not message: - logging.warning("An error has occurred without a message, setting default message") - message = "An error has occurred with error code (%s)" % str(code) - - logging.error(message) - logging.error("Stopping processing") - - result = {'error': message, 'code': code} - - return result - - @staticmethod - def load_metadata(metadata_path: str) -> dict: - """Loads the metadata from the specified path - Arguments: - metadata_path: path to the metadata file - Return: - Returns a dict containing the loaded metadata. If an error occurs, the dict - won't contain metadata but will contain an error message under an 'error' key. - """ - try: - if os.path.splitext(metadata_path)[1] in ('.yml', '.yaml'): - load_func = yaml.safe_load - else: - load_func = json.load - with open(metadata_path, 'r') as in_file: - md_load = load_func(in_file) - if md_load is not None: - md_return = {'metadata': md_load} - else: - msg = 'Invalid JSON/YAML specified in metadata file "%s"' % metadata_path - logging.error(msg) - md_return = {'error': msg} - except Exception as ex: - msg = "Unable to load metadata file '%s'" % metadata_path - logging.error(msg) - logging.error('Exception caught: %s', str(ex)) - if logging.getLogger().level == logging.DEBUG: - logging.exception(msg) - md_return = {'error': msg} - - return md_return - - @staticmethod - def check_params_result_error(transformer_params: dict) -> Optional[dict]: - """Checks the transformer parameter results for an error - Arguments: - transformer_params: the dictionary to check for errors - Return: - An error dict if errors were found and None if not - Notes: - See handle_error() function - """ - if 'code' in transformer_params: - if 'error' in transformer_params: - error = transformer_params['error'] - else: - error = "Error returned from get_transformer_params with code: %s" % transformer_params['code'] - return __internal__.handle_error(-104, error) - - return None - - @staticmethod - def check_retrieve_results_error(transformer_retrieve: tuple) -> Optional[dict]: - """Checks the results of the transformer_class retrieving files - Arguments: - transformer_retrieve: the results of the retrieve - Return: - An error dict if errors were found and None if not - Notes: - See handle_error() function - """ - if not transformer_retrieve: - return None - - code = 0 - message = None - retrieve_len = len(transformer_retrieve) - if retrieve_len > 0: - code = transformer_retrieve[0] - if retrieve_len > 1: - message = transformer_retrieve[1] - else: - message = "Retrieving files returned a code of %s" % str(code) - - # Check for an error code - if code < 0: - return __internal__.handle_error(code, message) - - # Log the message if we get one returned to us - if retrieve_len > 1: - logging.info(transformer_retrieve[1]) - - return None - - @staticmethod - def check_metadata_needed() -> bool: - """Checks if metadata is required - Return: - Returns True if metadata is required (the default is that it's required), or False if not - """ - # Disable the following check since it's not a valid test here (METADATA_NEEDED is an optional variable) - # pylint: disable=no-member - - # If we have a variable defined, check the many ways of determining False - if hasattr(configuration, "METADATA_NEEDED"): - if not configuration.METADATA_NEEDED: - return False - if isinstance(configuration.METADATA_NEEDED, str): - if configuration.METADATA_NEEDED.lower().strip() == 'false': - return False - return True - - @staticmethod - def load_metadata_files(metadata_files: list) -> dict: - """Loads the specified metadata files - Arguments: - metadata_files: list of metadata files to load - Returns: - Returns a dict containing the loaded metadata as an array. If an error occurs, the dict - won't contain metadata but will contain an error message under an 'error' key. - """ - metadata = [] - result = {'metadata': metadata} - for metadata_file in metadata_files: - if not os.path.exists(metadata_file): - result = __internal__.handle_error(-2, "Unable to access metadata file '%s'" % metadata_file) - break - logging.info("Loading metadata from file: '%s'", metadata_file) - md_loaded = __internal__.load_metadata(metadata_file) - if 'metadata' in md_loaded: - metadata.append(md_loaded['metadata']) - else: - result = __internal__.handle_error(-3, md_loaded['error']) - break - - return result - - @staticmethod - def parse_continue_result(result) -> tuple: - """Parses the result of calling transformer.check_continue and returns - the code and/or message - Arguments: - result: the result from calling transformer.check_continue - Return: - A tuple containing the result code and result message. One or both of these - values in the tuple may be None - Notes: - A string parameter will always return a result code of None and message of None indicating - the caller needs to decide what to do. - An integer parameter will cause the result message value of None, the caller needs to decide - what an appropriate message is. - A parameter that's iterable with a length > 0 will have the first value as the result code and the - second value as the result message. No checks are made for type conformity. - If the parameter is something other than the above, an exception will most likely be thrown. - """ - result_code = None - result_message = None - - if isinstance(result, int): - result_code = result - elif not isinstance(result, str): - result_len = len(result) - if result_len > 0: - result_code = result[0] - if result_len > 1: - result_message = result[1] - - return (result_code, result_message) - - @staticmethod - def handle_check_continue(transformer_instance: transformer_class.Transformer, transformer_params: dict) -> dict: - """Handles calling the transformer.check_continue function - Arguments: - transformer_instance: instance of Transformer class - transformer_params: dictionary of parameters to pass to transform module functions - Return: - Returns the result of checking to continue operation - """ - result = {} - - if hasattr(transformer, 'check_continue'): - check_result = transformer.check_continue(transformer_instance, **transformer_params) - result_code, result_message = __internal__.parse_continue_result(check_result) - - if result_code: - result['code'] = result_code - if result_message: - result['message'] = result_message - else: - logging.debug("transformer module doesn't have a function named 'check_continue'") - - return result - - @staticmethod - def handle_retrieve_files(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) ->\ - Optional[dict]: - """Handles calling the transformer class to retrieve files - Arguments: - transformer_instance: the current transformer environment - args: the command line arguments - metadata: the loaded metadata - Return: - A dict containing error information if a problem occurs and None if no problems are found. - Note: - A side effect of this function is a information message logged if the transformer class instance does not have - a 'retrieve_files' function declared. - """ - if hasattr(transformer_instance, 'retrieve_files'): - transformer_retrieve = transformer_instance.retrieve_files(args, metadata) - retrieve_results = __internal__.check_retrieve_results_error(transformer_retrieve) - if retrieve_results: - return retrieve_results - else: - logging.info("Transformer class doesn't have function named 'retrieve_files'") - - return None - - @staticmethod - def perform_processing(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) -> dict: - """Makes the calls to perform the processing - Arguments: - transformer_instance: instance of transformer class - args: the command line arguments - metadata: the loaded metadata - Return: - Returns a dict containing the result of processing - """ - result = {} - - # Get the various types of parameters from the transformer instance - if hasattr(transformer_instance, 'get_transformer_params'): - transformer_params = transformer_instance.get_transformer_params(args, metadata) - if not isinstance(transformer_params, dict): - return __internal__.handle_error(-101, - "Invalid return from getting transformer parameters from transformer class instance") - - params_result = __internal__.check_params_result_error(transformer_params) - if params_result: - return params_result - else: - logging.info("Transformer class instance does not have get_transformer_params method") - transformer_params = {} - - # First check if the transformer thinks everything is in place - if hasattr(transformer, 'check_continue'): - result = __internal__.handle_check_continue(transformer_instance, transformer_params) - if 'code' in result and result['code'] < 0 and 'error' not in result: - result['error'] = "Unknown error returned from check_continue call" - else: - logging.info("Transformer module doesn't have a function named 'check_continue'") - - # Retrieve additional files if indicated by return code from the check - if 'error' not in result and 'code' in result and result['code'] == 0: - result = __internal__.handle_retrieve_files(transformer_instance, args, metadata) - - # Next make the call to perform the processing - if 'error' not in result: - if hasattr(transformer, 'perform_process'): - result = transformer.perform_process(transformer_instance, **transformer_params) - else: - logging.debug("Transformer module is missing function named 'perform_process'") - return __internal__.handle_error(-102, "Transformer perform_process interface is not available " + - "for processing data") - - return result - - @staticmethod - def handle_result(result: dict, result_types: str = None, result_file_path: str = None) -> dict: - """Handles the results of processing as dictated by the arguments passed in. - Arguments: - result: the dictionary of result information - result_types: optional, comma separated string containing one or more of: all, file, print - result_file_path: optional, location to place result file - Return: - Returns the result parameter - Notes: - If result_types is None then no actions are taken. If 'file' or 'all' is specified - in result_types and result_file_path is None or empty, writing to a file is skipped - """ - if not result_types is None: - type_parts = [one_type.strip() for one_type in result_types.split(',')] - if 'print' in type_parts or 'all' in type_parts: - print(json.dumps(result, indent=2)) - if 'file' in type_parts or 'all' in type_parts: - if result_file_path: - os.makedirs(os.path.dirname(result_file_path), exist_ok=True) - with open(result_file_path, 'w') as out_file: - json.dump(result, out_file, indent=2) - else: - logging.warning("Writing result to a file was requested but a file path wasn't provided.") - logging.warning(" Skipping writing to a file.") - - return result - -def add_parameters(parser: argparse.ArgumentParser, transformer_instance) -> None: - """Function to prepare and execute work unit - Arguments: - parser: an instance of argparse.ArgumentParser - """ - parser.add_argument('--debug', '-d', action='store_const', - default=logging.WARN, const=logging.DEBUG, - help='enable debug logging (default=WARN)') - - parser.add_argument('--info', '-i', action='store_const', - default=logging.WARN, const=logging.INFO, - help='enable info logging (default=WARN)') - - parser.add_argument('--result', nargs='?', default='all', - help='Direct the result of a run to one or more of (all is default): "all,file,print"') - - parser.add_argument('--metadata', type=str, action='append', help='The path to the source metadata') - - parser.add_argument('--working_space', type=str, help='the folder to use use as a workspace and ' + - 'for storing results') - - # Let the transformer class add parameters - if hasattr(transformer_instance, 'add_parameters'): - transformer_instance.add_parameters(parser) - - # Check if the transformer has a function defined to extend command line arguments - if hasattr(transformer, 'add_parameters'): - transformer.add_parameters(parser) - - # Assume the rest of the arguments are the files - parser.add_argument('file_list', nargs=argparse.REMAINDER, help='additional files for transformer') - -def do_work(parser: argparse.ArgumentParser, **kwargs) -> dict: - """Function to prepare and execute work unit - Arguments: - parser: an instance of argparse.ArgumentParser - kwargs: keyword args - """ - result = {} - - # Create an instance of the transformer - transformer_instance = transformer_class.Transformer(**kwargs) - if not transformer_instance: - result = __internal__.handle_error(-100, "Unable to create transformer class instance for processing") - return __internal__.handle_result(result, None, None) - - add_parameters(parser, transformer_instance) - args = parser.parse_args() - - # start logging system - logging.getLogger().setLevel(args.debug if args.debug == logging.DEBUG else args.info) - - # Check that we have mandatory metadata - if not args.metadata and __internal__.check_metadata_needed(): - result = __internal__.handle_error(-1, "No metadata paths were specified.") - else: - md_results = __internal__.load_metadata_files(args.metadata) - if 'metadata' in md_results: - result = __internal__.perform_processing(transformer_instance, args, md_results['metadata']) - else: - result = __internal__.handle_error(-3, md_results['error']) - - if args.working_space: - result_path = os.path.join(args.working_space, 'result.json') - else: - result_path = None - - __internal__.handle_result(result, args.result, result_path) - return result - -if __name__ == "__main__": - try: - PARSER = argparse.ArgumentParser(description=configuration.TRANSFORMER_DESCRIPTION) - do_work(PARSER) - except Exception as ex: - logging.error("Top level exception handler caught an exception: %s", str(ex)) - raise diff --git a/generate_docker.py b/generate_docker.py deleted file mode 100755 index bf0cb4c..0000000 --- a/generate_docker.py +++ /dev/null @@ -1,69 +0,0 @@ -#!/usr/bin/env python3 - -"""Generated Dockerfile from a template -""" - -import argparse -import configuration - -# The template file name for Dockerfile -DOCKERFILE_TEMPLATE_FILE_NAMES = ["Dockerfile.template"] - -# The default docker image to use -DEFAULT_DOCKER_IMAGE = 'agpipeline/gantry-base-image:latest' - -def determine_base_image() -> str: - """Determines the base image to use in the dockerfile - Return: - The name of the base image to use - """ - parser = argparse.ArgumentParser() - - parser.add_argument('base_image', nargs='?', default=DEFAULT_DOCKER_IMAGE, - help='the docker image to use as the base for this transformer') - - args = parser.parse_args() - - return args.base_image - -def generate_dockerfile(base_image_name: str) -> None: - """Genertes a Dockerfile file using the configured information - """ - # pylint: disable=global-statement - global DOCKERFILE_TEMPLATE_FILE_NAMES - - missing = [] - if not hasattr(configuration, 'TRANSFORMER_NAME') or not configuration.TRANSFORMER_NAME: - missing.append("Transformer name") - if not hasattr(configuration, 'AUTHOR_NAME') or not configuration.AUTHOR_NAME: - missing.append("Author name") - if not hasattr(configuration, 'AUTHOR_EMAIL') or not configuration.AUTHOR_EMAIL: - missing.append("Author email") - if missing: - raise RuntimeError("One or more configuration fields aren't defined in configuration.py: " \ - + ", ".join(missing)) - - new_name = configuration.TRANSFORMER_NAME.strip().replace(' ', '_').replace('\t', '_').\ - replace('\n', '_').replace('\r', '_') - extractor_name = new_name.lower() - - for template_name in DOCKERFILE_TEMPLATE_FILE_NAMES: - template = [line.rstrip('\n') for line in open(template_name, "r")] - template_len = len('.template') - dockerfile_name = template_name[:(template_len * -1)] - with open(dockerfile_name, 'w') as out_file: - for line in template: - if line.startswith('LABEL maintainer='): - out_file.write("LABEL maintainer=\"{0} <{1}>\"\n".format(configuration.AUTHOR_NAME, \ - configuration.AUTHOR_EMAIL)) - elif line.startswith('FROM base-image'): - out_file.write("FROM {0}\n".format(base_image_name)) - else: - out_file.write("{0}\n".format(line)) - -# Make the call to generate the file -if __name__ == "__main__": - print('Configuring Dockerfile') - BASE = determine_base_image() - print('Using base image "%s"' % BASE) - generate_dockerfile(BASE) diff --git a/main.py b/main.py new file mode 100644 index 0000000..46119be --- /dev/null +++ b/main.py @@ -0,0 +1,27 @@ +import argparse +import pathlib +import soilmask + + +def main(): + parser = argparse.ArgumentParser( + description='Calculate a soil mask from a GeoTIFF') + parser.add_argument('filename', help='name of the file to process') + parser.add_argument('--output-file', default='soilmask-output.npz', + help='Path of the resulting output file') + parser.add_argument('--kernel-size', type=int, default=3, + help='masking kernel size') + args = parser.parse_args() + input_path = pathlib.Path(args.filename) + resolved_input_path = input_path.resolve(strict=True) + output_path = pathlib.Path(args.output_file) + + img_color = soilmask.load_image(resolved_input_path) + bin_mask = soilmask.gen_plant_mask(color_img=img_color, + kernel_size=args.kernel_size) + + soilmask.save_mask(output_path, bin_mask) + + +if __name__ == '__main__': + main() diff --git a/packages.txt b/packages.txt deleted file mode 100644 index 72b3e50..0000000 --- a/packages.txt +++ /dev/null @@ -1,4 +0,0 @@ -libsm6 -libxext6 -libxrender1 -libglib2.0-0 \ No newline at end of file diff --git a/recipe.scif b/recipe.scif index c32743d..24a8339 100644 --- a/recipe.scif +++ b/recipe.scif @@ -3,13 +3,13 @@ ~/miniconda3/bin/conda env create --prefix "${PWD}/conda" -f src/environment.yml # To regenerate src/environment.yml: - # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge opencv numpy + # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge py-opencv numpy # ~/miniconda3/bin/conda env export --prefix "${PWD}/conda" > src/environment.yml %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask - exec conda run --prefix "${SCIF_APPROOT}/conda" src/entrypoint.py "${@}" + exec conda run --prefix "${SCIF_APPROOT}/conda" src/main "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool docker run agpipeline/transformer-soilmask run soilmask \ No newline at end of file diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index abd49b6..0000000 --- a/requirements.txt +++ /dev/null @@ -1,2 +0,0 @@ -scikit-image -opencv-python diff --git a/soilmask.py b/soilmask.py new file mode 100644 index 0000000..05828d6 --- /dev/null +++ b/soilmask.py @@ -0,0 +1,45 @@ +import pathlib + +import numpy as np +import cv2 + +MAX_PIXEL_VAL = 255 + + +def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: + """Generates an image with plants masked in. + Arguments: + color_img: RGB image to mask + kernel_size: masking kernel size + Return: + An RGB image with plants masked in + """ + r_channel = color_img[:, :, 2] + g_channel = color_img[:, :, 1] + b_channel = color_img[:, :, 0] + + sub_img = (g_channel.astype('int') - r_channel.astype( + 'int') - 0) > 0 # normal: -2 + + mask = np.zeros_like(b_channel) + + mask[sub_img] = MAX_PIXEL_VAL + + blur = cv2.blur(mask, (kernel_size, kernel_size)) + pix = np.array(blur) + sub_mask = pix > 128 + + mask_1 = np.zeros_like(b_channel) + mask_1[sub_mask] = MAX_PIXEL_VAL + + return mask_1 + + +def load_image(image_path: pathlib.Path) -> np.ndarray: + img_raw = cv2.imread(str(image_path)) + color_img = cv2.cvtColor(img_raw, cv2.COLOR_BGR2RGB) + return color_img + + +def save_mask(output_path: pathlib.Path, bin_mask: np.ndarray): + np.savez_compressed(output_path, [bin_mask]) diff --git a/transformer.py b/transformer.py index 66aedee..e69de29 100644 --- a/transformer.py +++ b/transformer.py @@ -1,474 +0,0 @@ -"""Testing instance of transformer -""" - -import logging -import os -import tempfile -import numpy as np -import cv2 - -from osgeo import gdal -# from PIL import Image Used by code that's getting deprecated -from skimage import morphology - -from terrautils.formats import create_geotiff as tr_create_geotiff, \ - compress_geotiff as tr_compress_geotiff - -import configuration -import transformer_class - -SATURATE_THRESHOLD = 245 -MAX_PIXEL_VAL = 255 -SMALL_AREA_THRESHOLD = 200 - - -class __internal__(): - """Class for functions intended for internal use only for this file - """ - def __init__(self): - """Performs initialization of class instance - """ - -# @staticmethod -# def get_image_quality(imgfile: str) -> np.ndarray: -# """Computes and returns the image score for the image file -# Arguments: -# imgfile: the name of the file to compute the score for -# Returns: -# The score for the image -# """ -# img = Image.open(imgfile) -# img = np.array(img) -# -# nrmac = __internal__.MAC(img, img, img) -# -# return nrmac - - @staticmethod - def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: - """Generates an image with plants masked in. - Arguments: - color_img: RGB image to mask - kernel_size: masking kernel size - Return: - An RGB image with plants masked in - """ - r_channel = color_img[:, :, 2] - g_channel = color_img[:, :, 1] - b_channel = color_img[:, :, 0] - - sub_img = (g_channel.astype('int') - r_channel.astype('int') - 0) > 0 # normal: -2 - - mask = np.zeros_like(b_channel) - - mask[sub_img] = MAX_PIXEL_VAL - - blur = cv2.blur(mask, (kernel_size, kernel_size)) - pix = np.array(blur) - sub_mask = pix > 128 - - mask_1 = np.zeros_like(b_channel) - mask_1[sub_mask] = MAX_PIXEL_VAL - - return mask_1 - - @staticmethod - def remove_small_area_mask(mask_img: np.ndarray, min_area_size: int) -> np.ndarray: - """Removes small anomalies in the mask - Arguments: - mask_img: the mask image to remove anomalies from - min_area_size: the size of anomalies to look for - Return: - A new mask image with the anomalies removed - """ - mask_array = mask_img > 0 - rel_array = morphology.remove_small_objects(mask_array, min_area_size) - - rel_img = np.zeros_like(mask_img) - rel_img[rel_array] = MAX_PIXEL_VAL - - return rel_img - - @staticmethod - def remove_small_holes_mask(mask_image: np.ndarray, max_hole_size: int) -> np.ndarray: - """Removes small holes from the mask image - Arguments: - mask_image: the mask image to remove holes from - max_hole_size: the maximum size of holes to remove - Return: - A new mask image with the holes removed - """ - mask_array = mask_image > 0 - rel_array = morphology.remove_small_holes(mask_array, max_hole_size) - rel_img = np.zeros_like(mask_image) - rel_img[rel_array] = MAX_PIXEL_VAL - - return rel_img - - @staticmethod - def saturated_pixel_classification(gray_img: np.ndarray, base_mask: np.ndarray, saturated_mask: np.ndarray, - dilate_size: int = 0) -> np.ndarray: - """Returns an image with pixes classified for masking - Arguments: - Returns: - A mask image with the pixels classified - """ - # add saturated area into basic mask - saturated_mask = morphology.binary_dilation(saturated_mask, morphology.diamond(dilate_size)) - - rel_img = np.zeros_like(gray_img) - rel_img[saturated_mask] = MAX_PIXEL_VAL - - label_img, num = morphology.label(rel_img, connectivity=2, return_num=True) - - rel_mask = base_mask - - for idx in range(1, num): - match = (label_img == idx) - - if np.sum(match) > 100000: # if the area is too large, do not add it into basic mask - continue - - if not (match & base_mask).any(): - continue - - rel_mask = rel_mask | match - - return rel_mask - - @staticmethod - def over_saturation_process(rgb_image: np.ndarray, init_mask: np.ndarray, threshold: int = SATURATE_THRESHOLD) -> np.ndarray: - """Removes over saturated areas from an image - Arguments: - rgb_image: the image to process - init_mask: - threshold: The saturation threshold value - Return: - A new image with over saturated pixels removed - """ - # connected component analysis for over saturation pixels - gray_img = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY) - - mask_over = gray_img > threshold - - mask_0 = gray_img < threshold - - src_mask_array = init_mask > 0 - - mask_1 = src_mask_array & mask_0 - - mask_1 = morphology.remove_small_objects(mask_1, SMALL_AREA_THRESHOLD) - - mask_over = morphology.remove_small_objects(mask_over, SMALL_AREA_THRESHOLD) - - rel_mask = __internal__.saturated_pixel_classification(gray_img, mask_1, mask_over, 1) - rel_img = np.zeros_like(gray_img) - rel_img[rel_mask] = MAX_PIXEL_VAL - - return rel_img - - @staticmethod - def gen_saturated_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: - """Generates a mask of over saturated pixels - Arguments: - img: the image to generate the mask from - kernel_size: the size of masking kernel - Returns: - The image mask of over saturated pixels - """ - bin_mask = __internal__.gen_plant_mask(img, kernel_size) - bin_mask = __internal__.remove_small_area_mask(bin_mask, - 500) # 500 is a parameter for number of pixels to be removed as small area - bin_mask = __internal__.remove_small_holes_mask(bin_mask, - 300) # 300 is a parameter for number of pixels to be filled as small holes - - bin_mask = __internal__.over_saturation_process(img, bin_mask, SATURATE_THRESHOLD) - - bin_mask = __internal__.remove_small_holes_mask(bin_mask, 4000) - - return bin_mask - - @staticmethod - def gen_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: - """Generated the mask for plants - Arguments: - img: the image used to mask in plants - kernel_size: the size of the image processing kernel - Return: - A new image mask - """ - bin_mask = __internal__.gen_plant_mask(img, kernel_size) - bin_mask = __internal__.remove_small_area_mask(bin_mask, SMALL_AREA_THRESHOLD) - bin_mask = __internal__.remove_small_holes_mask(bin_mask, - 3000) # 3000 is a parameter for number of pixels to be filled as small holes - - return bin_mask - - @staticmethod - def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: - """Applies the mask to the image - Arguments: - img: the source image to mask - bin_mask: the mask to apply to the image - Return: - A new image that had the mask applied - """ - rgb_mask = cv2.bitwise_and(img, img, mask=bin_mask) - - return rgb_mask - -# @staticmethod -# def rgb2gray(rgb: np.ndarray) -> np.ndarray: -# """Converts RGB image to grey scale -# Arguments: -# rgb: the image to convert -# Return: -# The greyscale image -# """ -# r_channel, g_channel, b_channel = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2] -# gray = 0.2989 * r_channel + 0.5870 * g_channel + 0.1140 * b_channel -# return gray - -# @staticmethod -# def MAC(im1: np.ndarray, im2: np.ndarray, im: np.ndarray) -> np.ndarray: # pylint: disable=invalid-name -# """Calculates an image score of Multiscale Autocorrelation (MAC) -# Arguments: -# Return: -# Returns the scored image -# """ -# h_dim, _, c_dim = im1.shape -# if c_dim > 1: -# im = np.matrix.round(__internal__.rgb2gray(im)) -# im1 = np.matrix.round(__internal__.rgb2gray(im1)) -# im2 = np.matrix.round(__internal__.rgb2gray(im2)) -# # multiscale parameters -# scales = np.array([2, 3, 5]) -# fm_arr = np.zeros(len(scales)) -# for idx, _ in enumerate(scales): -# im1[0: h_dim - 1, :] = im[1:h_dim, :] -# im2[0: h_dim - scales[idx], :] = im[scales[idx]:h_dim, :] -# dif = im * (im1 - im2) -# fm_arr[idx] = np.mean(dif) -# nrmac = np.mean(fm_arr) -# return nrmac - - @staticmethod - def check_saturation(img: np.ndarray) -> list: - """Checks the saturation of an image - Arguments: - img: the image to check - Return: - A list containing the over threshold rate and the under threshold rate - """ - # check how many percent of pix close to 255 or 0 - gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - - over_threshold = gray_img > SATURATE_THRESHOLD - under_threshold = gray_img < 20 # 20 is a threshold to classify low pixel value - - over_rate = float(np.sum(over_threshold)) / float(gray_img.size) - low_rate = float(np.sum(under_threshold)) / float(gray_img.size) - - return over_rate, low_rate - -# @staticmethod -# def check_brightness(img: np.ndarray) -> float: -# """Generates average pixel value from grayscale image -# Arguments: -# img: the source image -# Returns: -# The average pixel value of the image -# """ -# gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) -# -# avg_value = np.average(gray_img) -# -# return avg_value - - @staticmethod - def get_maskfilename(filename: str) -> str: - """Returns the name of the file to use as a mask. Any path information - in the filename parameter is not returned. - Arguments: - filename: the name of the file to convert to a mask name - Return: - The name of the mask file - """ - base, ext = os.path.splitext(os.path.basename(filename)) - - return base + "_mask" + ext - - -def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> tuple: - """Generates an image mask keeping plants - Arguments: - input_path: the path to the input image - kernel_size: the image kernel size for processing - Return: - A list contianing the percent of unmasked pixels and the masked image - """ - # abandon low quality images, mask enhanced - # TODO: cv2 has problems with some RGB geotiffs... - # img = cv2.imread(input_path) - img = np.rollaxis(gdal.Open(input_path).ReadAsArray().astype(np.uint8), 0, 3) - img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) - - # calculate image scores - # pylint: disable=unused-variable - over_rate, low_rate = __internal__.check_saturation(img) - - # TODO: disabling this check for now because it's crashing extractor - generate mask regardless - # if low score, return None - # low_rate is percentage of low value pixels(lower than 20) in the grayscale image, if low_rate > 0.1, return - # aveValue is average pixel value of grayscale image, if aveValue lower than 30 or higher than 195, return - # quality_score is a score from Multiscale Autocorrelation (MAC), if quality_score lower than 13, return - - # saveValue = check_brightness(img) - # quality_score = get_image_quality(input_path) - # if low_rate > 0.1 or aveValue < 30 or aveValue > 195 or quality_score < 13: - # return None, None, None - - # saturated image process - # over_rate is percentage of high value pixels(higher than SATURATE_THRESHOLD) in the grayscale image, if - # over_rate > 0.15, try to fix it use gen_saturated_mask() - if over_rate > 0.15: - bin_mask = __internal__.gen_saturated_mask(img, kernel_size) - else: # normal image process - bin_mask = __internal__.gen_mask(img, kernel_size) - - count = np.count_nonzero(bin_mask) - ratio = count / float(bin_mask.size) - - rgb_mask = __internal__.gen_rgb_mask(img, bin_mask) - - return ratio, rgb_mask - - -def check_continue(transformer: transformer_class.Transformer, check_md: dict, transformer_md: list, - full_md: list) -> tuple: - """Checks if conditions are right for continuing processing - Arguments: - transformer: instance of transformer class - check_md: the metadata for this request - transformer_md: the metadata associated with this transformer - full_md: the full set of original metadata - Return: - Returns a tuple containing the return code for continuing or not, and - an error message if there's an error - """ - # pylint: disable=unused-argument - result = {'code': -1002, 'message': "No TIFF files were specified for processing"} - - # Ensure we have a TIFF file - if check_md and 'list_files' in check_md: - files = check_md['list_files']() - try: - for one_file in files: - ext = os.path.splitext(one_file)[1].lower() - if ext in ('.tiff', '.tif'): - result['code'] = 0 - break - except Exception as ex: - result['code'] = -1 - result['error'] = "Exception caught processing file list: %s" % str(ex) - else: - result['code'] = -1 - result['error'] = "Check metadata parameter is not configured to provide a list of files" - - return (result['code'], result['error']) if 'error' in result else (result['code']) - - -def perform_process(transformer: transformer_class.Transformer, check_md: dict, transformer_md: list, - full_md: list) -> dict: - """Performs the processing of the data - Arguments: - transformer: instance of transformer class' - check_md: the metadata for this request - transformer_md: the metadata associated with this transformer - full_md: the full set of original metadata - Return: - Returns a dictionary with the results of processing - """ - # pylint: disable=unused-argument - result = {} - file_md = [] - - # Loop through the files - try: - for one_file in check_md['list_files'](): - # Check file by type - ext = os.path.splitext(one_file)[1].lower() - if ext not in ('.tiff', '.tif'): - continue - if not os.path.exists(one_file): - logging.warning("Unable to access file '%s'", one_file) - continue - mask_source = one_file - - # Get the image's EPSG code - epsg = transformer.get_image_file_epsg(mask_source) - if epsg is None: - logging.debug("Skipping image that is not georeferenced: '%s'", mask_source) - continue - - # Check that it's geo referenced and transform it if it'sin the wrong coordinate system - if epsg != transformer.default_epsg: - logging.info("Reprojecting image from EPSG %s to default EPSG %s", str(epsg), - str(transformer.default_epsg)) - _, tmp_name = tempfile.mkstemp(dir=check_md['working_folder']) - src = gdal.Open(mask_source) - gdal.Warp(tmp_name, src, dstSRS='EPSG:'+str(transformer.default_epsg)) - mask_source = tmp_name - - # Get the bounds of the image to see if we can process it. - bounds = transformer.get_image_file_geobounds(mask_source) - - if bounds is None: - logging.warning("Unable to get bounds of georeferenced image: '%s'", - os.path.basename(one_file)) - if mask_source != one_file: - os.remove(mask_source) - continue - - # Get the mask name using the original name as reference - rgb_mask_tif = os.path.join(check_md['working_folder'], __internal__.get_maskfilename(one_file)) - - # Create the mask file - logging.debug("Creating mask file '%s'", rgb_mask_tif) - mask_ratio, mask_rgb = gen_cc_enhanced(mask_source) - - # Bands must be reordered to avoid swapping R and B - mask_rgb = cv2.cvtColor(mask_rgb, cv2.COLOR_BGR2RGB) - - transformer_info = transformer.generate_transformer_md() - - tr_create_geotiff(mask_rgb, bounds, rgb_mask_tif, None, False, - transformer_info, check_md['context_md']) - tr_compress_geotiff(rgb_mask_tif) - - # Remove any temporary file - if mask_source != one_file: - os.remove(mask_source) - - transformer_md = { - 'name': transformer_info['name'], - 'version': transformer_info['version'], - 'ratio': mask_ratio - } - - new_file_md = {'path': rgb_mask_tif, - 'key': configuration.TRANSFORMER_SENSOR, - 'metadata': { - 'data': transformer_md - } - } - file_md.append(new_file_md) - - result['code'] = 0 - result['file'] = file_md - - except Exception as ex: - result['code'] = -1001 - result['error'] = "Exception caught masking files: %s" % str(ex) - - return result diff --git a/transformer_class.py b/transformer_class.py deleted file mode 100644 index a4937e7..0000000 --- a/transformer_class.py +++ /dev/null @@ -1,261 +0,0 @@ -"""Class instance for Transformer -""" - -import os -import argparse -import datetime -import logging - -from terrautils.imagefile import get_epsg as tr_get_epsg, \ - image_get_geobounds as tr_image_get_geobounds -import terrautils.lemnatec -import piexif - -import configuration - -terrautils.lemnatec.SENSOR_METADATA_CACHE = os.path.dirname(os.path.realpath(__file__)) - -# EXIF tags to look for -EXIF_ORIGIN_TIMESTAMP = 36867 # Capture timestamp -EXIF_TIMESTAMP_OFFSET = 36881 # Timestamp UTC offset (general) -EXIF_ORIGIN_TIMESTAMP_OFFSET = 36881 # Capture timestamp UTC offset - - -class __internal__(): - """Class containing functions for this file only - """ - def __init__(self): - """Perform class level initialization - """ - - @staticmethod - def exif_tags_to_timestamp(exif_tags): - """Looks up the origin timestamp and a timestamp offset in the exit tags and returns - a datetime object - Args: - exif_tags(dict): The exif tags to search for timestamp information - Return: - Returns the origin timestamp when found. The return timestamp is adjusted for UTF if - an offset is found. None is returned if a valid timestamp isn't found. - """ - cur_stamp, cur_offset = (None, None) - - def convert_and_clean_tag(value): - """Internal helper function for handling EXIF tag values. Tests for an empty string after - stripping colons, '+', '-', and whitespace [the spec is unclear if a +/- is needed when - the timestamp offset is unknown (and spaces are used)]. - Args: - value(bytes or str): The tag value - Return: - Returns the cleaned up, and converted from bytes, string. Or None if the value is empty - after stripping above characters and whitespace. - """ - if not value: - return None - - # Convert bytes to string - if isinstance(value, bytes): - value = value.decode('UTF-8').strip() - else: - value = value.strip() - - # Check for an empty string after stripping colons - if value: - if not value.replace(":", "").replace("+:", "").replace("-", "").strip(): - value = None - - return None if not value else value - - # Process the EXIF data - if EXIF_ORIGIN_TIMESTAMP in exif_tags: - cur_stamp = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP]) - if not cur_stamp: - return None - - if EXIF_ORIGIN_TIMESTAMP_OFFSET in exif_tags: - cur_offset = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP_OFFSET]) - if not cur_offset and EXIF_TIMESTAMP_OFFSET in exif_tags: - cur_offset = convert_and_clean_tag(exif_tags[EXIF_TIMESTAMP_OFFSET]) - - # Format the string to a timestamp and return the result - try: - if not cur_offset: - cur_ts = datetime.datetime.fromisoformat(cur_stamp) - else: - cur_offset = cur_offset.replace(":", "") - cur_ts = datetime.datetime.fromisoformat(cur_stamp + cur_offset) - except Exception as ex: - cur_ts = None - logging.debug("Exception caught converting EXIF tag to timestamp: %s", str(ex)) - - return cur_ts - - @staticmethod - def get_first_timestamp(file_path: str, timestamp: str = None) -> str: - """Looks for a timestamp in the specified file and returns - the earliest timestamp (when compared to the timestamp parameter) - Arguments: - file_path: the path to the file to check - timestamp: the timestamp to compare against (when specified) - Return: - The earliest found timestamp - """ - first_stamp = datetime.datetime.fromisoformat(timestamp) if timestamp else None - try: - tags_dict = piexif.load(file_path) - if tags_dict and "Exif" in tags_dict: - cur_stamp = __internal__.exif_tags_to_timestamp(tags_dict["Exif"]) - if cur_stamp: - first_stamp = cur_stamp if first_stamp is None or cur_stamp < first_stamp else first_stamp - except Exception as ex: - logging.debug("Exception caught getting timestamp from file: %s", file_path) - logging.debug(" %s", str(ex)) - - if first_stamp: - return first_stamp.isoformat() - - return timestamp - - -class Transformer(): - """Generic class for supporting transformers - """ - - def __init__(self, **kwargs): - """Performs initialization of class instance - Arguments: - kwargs: additional parameters passed in to Transformer - """ - # pylint: disable=unused-argument - self.sensor = None - self.args = None - - @property - def default_epsg(self) -> int: - """Returns the current working EPSG code - """ - return 4326 - - @property - def supported_image_file_exts(self): - """Returns the list of supported image file extension strings (in lower case) - """ - return ['tif', 'tiff', 'jpg'] - - def get_image_file_epsg(self, source_path: str) -> str: - """Returns the EPSG of the georeferenced image file - Arguments: - source_path: the path to the image to load the EPSG code from - Return: - Returns the EPSG code loaded from the file. None is returned if there is a problem or the file - doesn't have an EPSG code - """ - # pylint: disable=no-self-use - return tr_get_epsg(source_path) - - def get_image_file_geobounds(self, source_path: str) -> list: - """Uses gdal functionality to retrieve rectilinear boundaries from the file - Args: - source_path(str): path of the file to get the boundaries from - Returns: - The upper-left and calculated lower-right boundaries of the image in a list upon success. - The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan - is returned if the boundaries can't be determined - """ - # pylint: disable=no-self-use - return tr_image_get_geobounds(source_path) - - def generate_transformer_md(self) -> dict: - """Generates metadata about this transformer - Returns: - Returns the transformer metadata - """ - # pylint: disable=no-self-use - return { - 'version': configuration.TRANSFORMER_VERSION, - 'name': configuration.TRANSFORMER_NAME, - 'author': configuration.AUTHOR_NAME, - 'description': configuration.TRANSFORMER_DESCRIPTION, - 'repository': {'repUrl': configuration.REPOSITORY} - } - - def add_parameters(self, parser: argparse.ArgumentParser) -> None: - """Adds processing parameters to existing parameters - Arguments: - parser: instance of argparse - """ - # pylint: disable=no-self-use - parser.epilog = configuration.TRANSFORMER_NAME + ' version ' + configuration.TRANSFORMER_VERSION + \ - ' author ' + configuration.AUTHOR_NAME + ' ' + configuration.AUTHOR_EMAIL - - def get_transformer_params(self, args: argparse.Namespace, metadata: list) -> dict: - """Returns a parameter list for processing data - Arguments: - args: result of calling argparse.parse_args - metadata: the loaded metadata - """ - # Disabling this warning to keep code readable - # pylint: disable=too-many-branches - self.args = args - - timestamp, season_name, experiment_name = None, None, None - parsed_metadata = [] - transformer_md = [] - - # Loop through the metadata - for one_metadata in metadata: - # Determine if we're using JSONLD - if 'content' in one_metadata: - parse_md = one_metadata['content'] - else: - parse_md = one_metadata - # Check for legacy 'pipeline' key - if 'pipeline' in parse_md: - parse_md = parse_md['pipeline'] - parsed_metadata.append(parse_md) - - # Get the season, experiment, etc information - if 'observationTimeStamp' in parse_md: - timestamp = parse_md['observationTimeStamp'] - if 'season' in parse_md: - season_name = parse_md['season'] - if 'studyName' in parse_md: - experiment_name = parse_md['studyName'] - - # Check for transformer specific metadata - if configuration.TRANSFORMER_NAME in parse_md: - if isinstance(parse_md[configuration.TRANSFORMER_NAME], list): - transformer_md.extend(parse_md[configuration.TRANSFORMER_NAME]) - else: - transformer_md.append(parse_md[configuration.TRANSFORMER_NAME]) - # Get the list of files, if there are some and find the earliest timestamp if a timestamp - # hasn't been specified yet - file_list = [] - working_timestamp = timestamp - if args.file_list: - for one_file in args.file_list: - # Filter out arguments that are obviously not files - if not one_file.startswith('-'): - file_list.append(one_file) - # Only bother to get a timestamp if we don't have one specified - if timestamp is None: - working_timestamp = __internal__.get_first_timestamp(one_file, working_timestamp) - if timestamp is None and working_timestamp is not None: - timestamp = working_timestamp - - # Prepare our parameters - check_md = {'timestamp': timestamp, - 'season': season_name, - 'experiment': experiment_name, - 'container_name': None, - 'target_container_name': None, - 'trigger_name': None, - 'context_md': None, - 'working_folder': args.working_space, - 'list_files': lambda: file_list - } - - return {'check_md': check_md, - 'transformer_md': transformer_md, - 'full_md': parsed_metadata - } From dbd17c8e73f895aa9384f9c850056faf730407fd Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 7 May 2020 17:54:48 -0700 Subject: [PATCH 17/42] Fixed FROM in Dockerfile --- Dockerfile | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/Dockerfile b/Dockerfile index 20bb0e3..35ccfd9 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,5 +1,4 @@ -#FROM phusion/baseimage -FROM agdrone/transformer-opendronemap:3.0 +FROM phusion/baseimage # Env variables ENV DEBIAN_FRONTEND noninteractive From 16461d517073d4a2e43ba03f46446731b2fbb8e6 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 7 May 2020 18:03:52 -0700 Subject: [PATCH 18/42] Fixed path to main.py --- recipe.scif | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipe.scif b/recipe.scif index 24a8339..1ac342b 100644 --- a/recipe.scif +++ b/recipe.scif @@ -9,7 +9,7 @@ %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask - exec conda run --prefix "${SCIF_APPROOT}/conda" src/main "${@}" + exec conda run --prefix "${SCIF_APPROOT}/conda" src/main.py "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool docker run agpipeline/transformer-soilmask run soilmask \ No newline at end of file From f4321a262206933c23f34a015516e64e344bc939 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 7 May 2020 18:42:21 -0700 Subject: [PATCH 19/42] Added python3 to the conda command. --- recipe.scif | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipe.scif b/recipe.scif index 1ac342b..8435de3 100644 --- a/recipe.scif +++ b/recipe.scif @@ -9,7 +9,7 @@ %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask - exec conda run --prefix "${SCIF_APPROOT}/conda" src/main.py "${@}" + exec conda run --prefix "${SCIF_APPROOT}/conda" python3 src/main.py "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool docker run agpipeline/transformer-soilmask run soilmask \ No newline at end of file From 031401bc3cf3c866ae66ac15d9142eb2dd9af16b Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 7 May 2020 19:05:32 -0700 Subject: [PATCH 20/42] Generate SCIF help section by running: main.py --help --- recipe.scif | 3 +++ 1 file changed, 3 insertions(+) diff --git a/recipe.scif b/recipe.scif index 8435de3..5648016 100644 --- a/recipe.scif +++ b/recipe.scif @@ -6,6 +6,9 @@ # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge py-opencv numpy # ~/miniconda3/bin/conda env export --prefix "${PWD}/conda" > src/environment.yml + echo "\n" >> "${PWD}/scif/runscript.help" + ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 src/main.py --help >> "${PWD}/scif/runscript.help" + %appenv soilmask PATH=~/miniconda3/bin:$PATH %apprun soilmask From b785ee9ad7652a4c418971db93dd4a60ebd0e450 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 7 May 2020 19:35:33 -0700 Subject: [PATCH 21/42] Add example Docker command to SCIF app help section. Can be overridden by setting an environment variable in your Dockerfile like so: ENV DOCKER_IMAGE agpipeline/my-drone-pipeline:1.0 --- recipe.scif | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/recipe.scif b/recipe.scif index 5648016..53bb2de 100644 --- a/recipe.scif +++ b/recipe.scif @@ -6,7 +6,11 @@ # ~/miniconda3/bin/conda create --prefix "${PWD}/conda" --yes -c conda-forge py-opencv numpy # ~/miniconda3/bin/conda env export --prefix "${PWD}/conda" > src/environment.yml - echo "\n" >> "${PWD}/scif/runscript.help" + # Add example Docker command to SCIF app help section + test -z $DOCKER_IMAGE && DOCKER_IMAGE="agpipeline/soilmask:latest" + echo "\n\nExample Docker command: docker run $DOCKER_IMAGE run soilmask\n" >> "${PWD}/scif/runscript.help" + + # Generate remainder of SCIF app help section by running: src/main.py --help ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 src/main.py --help >> "${PWD}/scif/runscript.help" %appenv soilmask @@ -15,4 +19,3 @@ exec conda run --prefix "${SCIF_APPROOT}/conda" python3 src/main.py "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool - docker run agpipeline/transformer-soilmask run soilmask \ No newline at end of file From 2d3cc178280d0bbf4f2a79d69c16c4e145a7ea12 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Thu, 7 May 2020 23:56:31 -0700 Subject: [PATCH 22/42] Removed unnecessary PATH environment variable. --- recipe.scif | 2 -- 1 file changed, 2 deletions(-) diff --git a/recipe.scif b/recipe.scif index 53bb2de..80ef535 100644 --- a/recipe.scif +++ b/recipe.scif @@ -13,8 +13,6 @@ # Generate remainder of SCIF app help section by running: src/main.py --help ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 src/main.py --help >> "${PWD}/scif/runscript.help" -%appenv soilmask - PATH=~/miniconda3/bin:$PATH %apprun soilmask exec conda run --prefix "${SCIF_APPROOT}/conda" python3 src/main.py "${@}" %apphelp soilmask From 119321f799865d86771dfb378b005bb9e75810f9 Mon Sep 17 00:00:00 2001 From: Julian Pistorius Date: Fri, 8 May 2020 00:52:59 -0700 Subject: [PATCH 23/42] When I removed the appenv section it broke the path to conda. Hard-coding it now. --- recipe.scif | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/recipe.scif b/recipe.scif index 80ef535..f6e72c7 100644 --- a/recipe.scif +++ b/recipe.scif @@ -14,6 +14,6 @@ ~/miniconda3/bin/conda run --prefix "${PWD}/conda" python3 src/main.py --help >> "${PWD}/scif/runscript.help" %apprun soilmask - exec conda run --prefix "${SCIF_APPROOT}/conda" python3 src/main.py "${@}" + exec ~/miniconda3/bin/conda run --prefix "${SCIF_APPROOT}/conda" python3 src/main.py "${@}" %apphelp soilmask This app provides an entrypoint to the soilmask tool From 7325f522541995cd9391100e3fc0ce8eba7c5795 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 18 May 2020 11:18:59 -0700 Subject: [PATCH 24/42] Making drone-only (#13) --- Dockerfile | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/Dockerfile b/Dockerfile index f107ccf..52fbf01 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,6 +1,4 @@ -# Version 1.0 template-transformer-simple - -FROM agpipeline/gantry-base-image:latest +FROM FROM agdrone/drone-base-image:1.2 LABEL maintainer="Chris Schnaufer " COPY requirements.txt packages.txt /home/extractor/ From e8243d2cb5604a8249add0b47f9756627926741d Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Wed, 13 May 2020 14:12:42 -0700 Subject: [PATCH 25/42] Updated to produce geotiff --- environment.yml | 3 + main.py | 8 ++- soilmask.py | 161 ++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 171 insertions(+), 1 deletion(-) diff --git a/environment.yml b/environment.yml index cf5ae2d..11c9b79 100644 --- a/environment.yml +++ b/environment.yml @@ -87,4 +87,7 @@ dependencies: - xz=5.2.5=h516909a_0 - zlib=1.2.11=h516909a_1006 - zstd=1.4.4=h6597ccf_3 + - pip: + - gdal==2.2.2 + - setuptools==46.2.0 prefix: /scif/apps/soilmask/conda \ No newline at end of file diff --git a/main.py b/main.py index 46119be..4cb3822 100644 --- a/main.py +++ b/main.py @@ -1,6 +1,7 @@ import argparse import pathlib import soilmask +import cv2 def main(): @@ -16,11 +17,16 @@ def main(): resolved_input_path = input_path.resolve(strict=True) output_path = pathlib.Path(args.output_file) + bounds = soilmask.get_image_file_geobounds(resolved_input_path) + img_color = soilmask.load_image(resolved_input_path) bin_mask = soilmask.gen_plant_mask(color_img=img_color, kernel_size=args.kernel_size) - soilmask.save_mask(output_path, bin_mask) + rgb_mask = soilmask.gen_rgb_mask(img_color, bin_mask) + mask_rgb = cv2.cvtColor(rgb_mask, cv2.COLOR_BGR2RGB) + + soilmask.create_geotiff(mask_rgb, bounds, output_path, nodata=None, asfloat=False) if __name__ == '__main__': diff --git a/soilmask.py b/soilmask.py index 05828d6..e687349 100644 --- a/soilmask.py +++ b/soilmask.py @@ -1,11 +1,27 @@ import pathlib import numpy as np +import logging import cv2 +import tempfile +from osgeo import gdal, osr MAX_PIXEL_VAL = 255 +def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: + """Applies the mask to the image + Arguments: + img: the source image to mask + bin_mask: the mask to apply to the image + Return: + A new image that had the mask applied + """ + rgb_mask = cv2.bitwise_and(img, img, mask=bin_mask) + + return rgb_mask + + def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: """Generates an image with plants masked in. Arguments: @@ -34,6 +50,151 @@ def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: return mask_1 +def get_epsg(filename): + """Returns the EPSG of the georeferenced image file + Args: + filename(str): path of the file to retrieve the EPSG code from + Return: + Returns the found EPSG code, or None if it's not found or an error ocurred + """ + logger = logging.getLogger(__name__) + + try: + src = gdal.Open(filename) + + proj = osr.SpatialReference(wkt=src.GetProjection()) + + return proj.GetAttrValue('AUTHORITY', 1) + # pylint: disable=broad-except + except Exception as ex: + logger.warn("[get_epsg] Exception caught: %s", str(ex)) + # pylint: enable=broad-except + + return None + + +def get_image_file_geobounds(filename): + """Uses gdal functionality to retrieve rectilinear boundaries from the file + Args: + filename(str): path of the file to get the boundaries from + Returns: + The upper-left and calculated lower-right boundaries of the image in a list upon success. + The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan + is returned if the boundaries can't be determined + """ + try: + str_filename = str(filename) + epsg = get_epsg(str_filename) + if str(epsg) != "4326": + _, tmp_name = tempfile.mkstemp() + src = gdal.Open(str_filename) + gdal.Warp(tmp_name, src, dstSRS='EPSG:4326') + str_filename = tmp_name + + src = gdal.Open(str_filename) + ulx, xres, _, uly, _, yres = src.GetGeoTransform() + lrx = ulx + (src.RasterXSize * xres) + lry = uly + (src.RasterYSize * yres) + + min_y = min(uly, lry) + max_y = max(uly, lry) + min_x = min(ulx, lrx) + max_x = max(ulx, lrx) + + return [min_y, max_y, min_x, max_x] + except Exception as ex: + logging.info("[image_get_geobounds] Exception caught: %s", str(ex)) + + return [np.nan, np.nan, np.nan, np.nan] + + +def create_geotiff(pixels, gps_bounds, out_path, nodata=-99, asfloat=False, extractor_info=None, system_md=None, + extra_metadata=None, compress=True): + """Generate output GeoTIFF file given a numpy pixel array and GPS boundary. + Keyword arguments: + pixels -- numpy array of pixel values. + if 2-dimensional array, a single-band GeoTIFF will be created. + if 3-dimensional array, a band will be created for each Z dimension. + gps_bounds -- tuple of GeoTIFF coordinates as ( lat (y) min, lat (y) max, + long (x) min, long (x) max) + out_path -- path to GeoTIFF to be created + nodata -- NoDataValue to be assigned to raster bands; set to None to ignore + float -- whether to use GDT_Float32 data type instead of GDT_Byte (e.g. for decimal numbers) + extractor_info -- details about extractor if applicable + system_md -- cleaned TERRA-REF metadata + extra_metadata -- any metadata to be embedded in geotiff; supersedes extractor_info and system_md + """ + dimensions = np.shape(pixels) + if len(dimensions) == 2: + nrows, ncols = dimensions + channels = 1 + else: + nrows, ncols, channels = dimensions + + geotransform = ( + gps_bounds[2], # upper-left x + (gps_bounds[3] - gps_bounds[2])/float(ncols), # W-E pixel resolution + 0, # rotation (0 = North is up) + gps_bounds[1], # upper-left y + 0, # rotation (0 = North is up) + -((gps_bounds[1] - gps_bounds[0])/float(nrows)) # N-S pixel resolution + ) + + # Create output GeoTIFF and set coordinates & projection + if asfloat: + dtype = gdal.GDT_Float32 + else: + dtype = gdal.GDT_Byte + + if compress: + output_raster = gdal.GetDriverByName('GTiff') \ + .Create(str(out_path), ncols, nrows, channels, dtype, ['COMPRESS=LZW']) + else: + output_raster = gdal.GetDriverByName('GTiff') \ + .Create(str(out_path), ncols, nrows, channels, dtype) + + output_raster.SetGeoTransform(geotransform) + srs = osr.SpatialReference() + srs.ImportFromEPSG(4326) # google mercator + output_raster.SetProjection( srs.ExportToWkt() ) + + if channels == 3: + # typically 3 channels = RGB channels + # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels) + output_raster.GetRasterBand(1).WriteArray(pixels[:,:,0].astype('uint8')) + output_raster.GetRasterBand(1).SetColorInterpretation(gdal.GCI_RedBand) + output_raster.GetRasterBand(1).FlushCache() + if nodata: + output_raster.GetRasterBand(1).SetNoDataValue(nodata) + + output_raster.GetRasterBand(2).WriteArray(pixels[:,:,1].astype('uint8')) + output_raster.GetRasterBand(2).SetColorInterpretation(gdal.GCI_GreenBand) + output_raster.GetRasterBand(2).FlushCache() + if nodata: + output_raster.GetRasterBand(2).SetNoDataValue(nodata) + + output_raster.GetRasterBand(3).WriteArray(pixels[:,:,2].astype('uint8')) + output_raster.GetRasterBand(3).SetColorInterpretation(gdal.GCI_BlueBand) + output_raster.GetRasterBand(3).FlushCache() + if nodata: + output_raster.GetRasterBand(3).SetNoDataValue(nodata) + + elif channels > 1: + # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels) + for chan in range(channels): + band = chan + 1 + output_raster.GetRasterBand(band).WriteArray(pixels[:,:,chan].astype('uint8')) + output_raster.GetRasterBand(band).FlushCache() + if nodata: + output_raster.GetRasterBand(band).SetNoDataValue(nodata) + else: + # single channel image, e.g. temperature + output_raster.GetRasterBand(1).WriteArray(pixels) + output_raster.GetRasterBand(1).FlushCache() + if nodata: + output_raster.GetRasterBand(1).SetNoDataValue(nodata) + + output_raster = None def load_image(image_path: pathlib.Path) -> np.ndarray: img_raw = cv2.imread(str(image_path)) From 0f0640912684a77ac720a180007898c4e8fceaac Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Fri, 5 Jun 2020 13:47:15 -0700 Subject: [PATCH 26/42] Adding pylint workflow --- .github/workflows/pylint_check.yaml | 83 +++++++++++++++++++++++++++++ action_pylint.sh | 3 ++ actions_github/README.md | 4 ++ actions_github/transformer_class.py | 49 +++++++++++++++++ generate_docker.py | 4 -- 5 files changed, 139 insertions(+), 4 deletions(-) create mode 100644 .github/workflows/pylint_check.yaml create mode 100644 action_pylint.sh create mode 100644 actions_github/README.md create mode 100644 actions_github/transformer_class.py diff --git a/.github/workflows/pylint_check.yaml b/.github/workflows/pylint_check.yaml new file mode 100644 index 0000000..e7ab1a6 --- /dev/null +++ b/.github/workflows/pylint_check.yaml @@ -0,0 +1,83 @@ +name: Enforcing pylint checks +on: + push: + branches: + - master + - develop + - pylint_workflow + pull_request: + branches: + - master + - develop + tags: + - v* + +jobs: + update_python: + runs-on: ubuntu-latest + name: Running pylint checks + steps: + - name: Current python version + run: python3 --version || echo python3 not installed + - name: Install Python 3.7 + run: sudo apt-get install -y --no-install-recommends python3.7 python3-pip && sudo ln -sfn /usr/bin/python3.7 /usr/bin/python3 + id: install_python_3_7 + - name: Updated python version + run: python3 --version + - name: PYTHONPATH environment variable + run: echo ${PYTHONPATH} + - name: Update pip + run: python3 -m pip install --upgrade --no-cache-dir pip + id: pip-install + - name: Fetch/update setuptools + run: python3 -m pip install --upgrade --no-cache-dir setuptools + id: setuptools-install + - name: Install python-apt + run: sudo apt-get install -y python-apt + - name: HACK to fix apt-get update problem w/ different python versions + run: 'cd /usr/lib/python3/dist-packages && sudo cp apt_pkg.cpython-36m-x86_64-linux-gnu.so apt_pkg.so' + - name: Update apt-get + run: sudo apt-get update + - name: Fetch/update pylint + run: python3 -m pip install --upgrade --no-cache-dir pylint + id: pylint-install + - name: Fetch source code + uses: actions/checkout@v2 + id: fetch-source + - name: Finding files + run: find . -type f -name "*.py" > action_pylint_files.txt + id: find-python-files + - name: Install system requirements + shell: bash + run: 'sudo apt-get install -y python3-gdal gdal-bin libgdal-dev gcc g++ python3.7-dev' + id: install-gdal-other-reqs + - name: Install Python numpy + shell: bash + run: 'python3 -m pip install --upgrade --no-cache-dir numpy wheel terrautils' + id: install-python-numpy + - name: Install Python pygdal + shell: bash + run: 'sudo python3 -m pip install --no-cache-dir pygdal==2.2.3.5' + id: install-python-pygdal + - name: Install system requirements from source + shell: bash + run: '[ -s "packages.txt" ] && (cat packages.txt | xargs apt-get install -y --no-install-recommends) || (echo "No addtional packages to install")' + id: install-system-reqs + - name: Install Python requirements from source + shell: bash + run: '[ -s "requirements.txt" ] && (python3 -m pip install --no-cache-dir -r requirements.txt) || (echo "No Python packages to install")' + id: install-python-reqs + - name: Run action pylint script + shell: bash + run: '[ -s "action_pylint.sh" ] && (chmod +x "action_pylint.sh" && ./action_pylint.sh) || (echo "Not running special action script - empty or not found")' + id: run-special-action-script + - name: Fetching pylint.rc file + run: wget https://raw.githubusercontent.com/AgPipeline/Organization-info/master/pylint.rc + id: fetch_pylint_resource + - name: Listing + run: ls -la + - name: Files to be linted + run: cat action_pylint_files.txt + - name: Running pylint + run: cat action_pylint_files.txt | xargs python3 -m pylint --rcfile ./pylint.rc + diff --git a/action_pylint.sh b/action_pylint.sh new file mode 100644 index 0000000..4fed995 --- /dev/null +++ b/action_pylint.sh @@ -0,0 +1,3 @@ +#!/bin/bash +cp ./actions_github/* ./ + diff --git a/actions_github/README.md b/actions_github/README.md new file mode 100644 index 0000000..47ae351 --- /dev/null +++ b/actions_github/README.md @@ -0,0 +1,4 @@ +# Github Actions Support Folder + +This folder contains files used to support GitHub actions and workflows + diff --git a/actions_github/transformer_class.py b/actions_github/transformer_class.py new file mode 100644 index 0000000..56417e2 --- /dev/null +++ b/actions_github/transformer_class.py @@ -0,0 +1,49 @@ +"""Class instance for Transformer +""" + +import argparse + +# pylint: disable=unused-argument +class Transformer(): + """Generic class for supporting transformers + """ + def __init__(self, **kwargs): + """Performs initialization of class instance + Arguments: + kwargs: additional parameters passed into Transformer instance + """ + self.args = None + + def add_parameters(self, parser: argparse.ArgumentParser) -> None: + """Adds processing parameters to existing parameters + Arguments: + parser: instance of argparse + """ + + # pylint: disable=no-self-use + def get_transformer_params(self, args: argparse.Namespace, metadata: list) -> dict: + """Returns a parameter list for processing data + Arguments: + args: result of calling argparse.parse_args + metadata: the list of loaded metadata + Return: + A dictionary of parameter names and value to pass to transformer + """ + self.args = args + + params = {} + return params + + # pylint: disable=no-self-use + def retrieve_files(self, transformer_params: dict, metadata: list) -> tuple: + """Retrieves files as needed to make them available for processing + Arguments: + transformer_params: the values returned from get_transformer_params() call + metadata: the loaded metadata + Return: + A tuple consisting of the return code and an optional error message. + Notes: + A negative return code is considered an error and an associated message, if specified, + will be treated as such. + """ + return 0, "everything's in order" diff --git a/generate_docker.py b/generate_docker.py index bf0cb4c..c5b0a7d 100755 --- a/generate_docker.py +++ b/generate_docker.py @@ -43,10 +43,6 @@ def generate_dockerfile(base_image_name: str) -> None: raise RuntimeError("One or more configuration fields aren't defined in configuration.py: " \ + ", ".join(missing)) - new_name = configuration.TRANSFORMER_NAME.strip().replace(' ', '_').replace('\t', '_').\ - replace('\n', '_').replace('\r', '_') - extractor_name = new_name.lower() - for template_name in DOCKERFILE_TEMPLATE_FILE_NAMES: template = [line.rstrip('\n') for line in open(template_name, "r")] template_len = len('.template') From f7669ca6aaa08bfa7a75f06b75cc53bb83be4947 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Fri, 5 Jun 2020 13:54:13 -0700 Subject: [PATCH 27/42] Working around opencv & pylint problem --- .github/workflows/pylint_check.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pylint_check.yaml b/.github/workflows/pylint_check.yaml index e7ab1a6..23fe99c 100644 --- a/.github/workflows/pylint_check.yaml +++ b/.github/workflows/pylint_check.yaml @@ -79,5 +79,5 @@ jobs: - name: Files to be linted run: cat action_pylint_files.txt - name: Running pylint - run: cat action_pylint_files.txt | xargs python3 -m pylint --rcfile ./pylint.rc + run: cat action_pylint_files.txt | xargs python3 -m pylint --rcfile ./pylint.rc --extension-pkg-whitelist=cv2 From 4509c2e9f3c5f7002394ec21fca3bd953ca719a8 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Fri, 5 Jun 2020 14:00:43 -0700 Subject: [PATCH 28/42] Removing branch from workflow file --- .github/workflows/pylint_check.yaml | 1 - 1 file changed, 1 deletion(-) diff --git a/.github/workflows/pylint_check.yaml b/.github/workflows/pylint_check.yaml index 23fe99c..e26eb2b 100644 --- a/.github/workflows/pylint_check.yaml +++ b/.github/workflows/pylint_check.yaml @@ -4,7 +4,6 @@ on: branches: - master - develop - - pylint_workflow pull_request: branches: - master From 2cc8cad41534d6a6a6af7e672d42e84bf6250bec Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 8 Jun 2020 12:07:57 -0700 Subject: [PATCH 29/42] Moving files --- {actions_github => .github/workflows}/README.md | 0 action_pylint.sh => .github/workflows/action_pylint.sh | 0 {actions_github => .github/workflows}/transformer_class.py | 0 3 files changed, 0 insertions(+), 0 deletions(-) rename {actions_github => .github/workflows}/README.md (100%) rename action_pylint.sh => .github/workflows/action_pylint.sh (100%) rename {actions_github => .github/workflows}/transformer_class.py (100%) diff --git a/actions_github/README.md b/.github/workflows/README.md similarity index 100% rename from actions_github/README.md rename to .github/workflows/README.md diff --git a/action_pylint.sh b/.github/workflows/action_pylint.sh similarity index 100% rename from action_pylint.sh rename to .github/workflows/action_pylint.sh diff --git a/actions_github/transformer_class.py b/.github/workflows/transformer_class.py similarity index 100% rename from actions_github/transformer_class.py rename to .github/workflows/transformer_class.py From 98d3378dad14d9dd5466c4be436ebf9130f6c14b Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 8 Jun 2020 12:14:05 -0700 Subject: [PATCH 30/42] Clean up level folder --- .github/workflows/action_pylint.sh | 2 +- .github/workflows/pylint_check.yaml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/action_pylint.sh b/.github/workflows/action_pylint.sh index 4fed995..07b5863 100644 --- a/.github/workflows/action_pylint.sh +++ b/.github/workflows/action_pylint.sh @@ -1,3 +1,3 @@ #!/bin/bash -cp ./actions_github/* ./ +cp ./.github/workflows/actions_github/*.py ./ diff --git a/.github/workflows/pylint_check.yaml b/.github/workflows/pylint_check.yaml index e26eb2b..1774738 100644 --- a/.github/workflows/pylint_check.yaml +++ b/.github/workflows/pylint_check.yaml @@ -68,7 +68,7 @@ jobs: id: install-python-reqs - name: Run action pylint script shell: bash - run: '[ -s "action_pylint.sh" ] && (chmod +x "action_pylint.sh" && ./action_pylint.sh) || (echo "Not running special action script - empty or not found")' + run: '[ -s ".github/workflows/action_pylint.sh" ] && (chmod +x ".github/workflows/action_pylint.sh" && ./.github/workflows/action_pylint.sh) || (echo "Not running special action script - empty or not found")' id: run-special-action-script - name: Fetching pylint.rc file run: wget https://raw.githubusercontent.com/AgPipeline/Organization-info/master/pylint.rc From 91bd86822f99d44cf9a6fba6a8dafc03a0a9f13a Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 8 Jun 2020 12:36:26 -0700 Subject: [PATCH 31/42] Fixing copy command --- .github/workflows/action_pylint.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/action_pylint.sh b/.github/workflows/action_pylint.sh index 07b5863..598a1fd 100644 --- a/.github/workflows/action_pylint.sh +++ b/.github/workflows/action_pylint.sh @@ -1,3 +1,3 @@ #!/bin/bash -cp ./.github/workflows/actions_github/*.py ./ +cp ./.github/workflows/*.py ./ From 0baea37dc6e566ae7035af64a0a0b8ad455b4968 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 8 Jun 2020 12:47:47 -0700 Subject: [PATCH 32/42] Fixed message and removed unneeded README --- .github/workflows/README.md | 4 ---- 1 file changed, 4 deletions(-) delete mode 100644 .github/workflows/README.md diff --git a/.github/workflows/README.md b/.github/workflows/README.md deleted file mode 100644 index 47ae351..0000000 --- a/.github/workflows/README.md +++ /dev/null @@ -1,4 +0,0 @@ -# Github Actions Support Folder - -This folder contains files used to support GitHub actions and workflows - From 2047f91dedd48b12887fafb021ccdae5842944fa Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Wed, 10 Jun 2020 10:25:30 -0700 Subject: [PATCH 33/42] updating for scif --- entrypoint.py | 409 +++++++++++++++++++++++++++++++++++++++++++ transformer.py | 136 +++++++++++++- transformer_class.py | 311 ++++++++++++++++++++++++++++++++ 3 files changed, 849 insertions(+), 7 deletions(-) create mode 100755 entrypoint.py create mode 100644 transformer_class.py diff --git a/entrypoint.py b/entrypoint.py new file mode 100755 index 0000000..2db27cb --- /dev/null +++ b/entrypoint.py @@ -0,0 +1,409 @@ +#!/usr/bin/env python3 +"""Base entry point for Agriculture Pipeline transformer +""" + +import argparse +import os +import json +import logging +from typing import Optional +import yaml + +import transformer_class + +# From derived images +import configuration +import transformer + +class __internal__(): + """Class for functions intended for internal use only for this file + """ + def __init__(self): + """Performs initialization of class instance + """ + + @staticmethod + def handle_error(code: int, message: str) -> dict: + """Handles logging and return values when an error occurs. Implies processing + will stop. + Arguments: + code: return code related to the error + message: the message string of the error + Return: + Returns a dict with the code and message + """ + if code is None: + logging.warning("An error has occurred without a return code specified, setting default return code") + code = -1 + if not message: + logging.warning("An error has occurred without a message, setting default message") + message = "An error has occurred with error code (%s)" % str(code) + + logging.error(message) + logging.error("Stopping processing") + + result = {'error': message, 'code': code} + + return result + + @staticmethod + def load_metadata(metadata_path: str) -> dict: + """Loads the metadata from the specified path + Arguments: + metadata_path: path to the metadata file + Return: + Returns a dict containing the loaded metadata. If an error occurs, the dict + won't contain metadata but will contain an error message under an 'error' key. + """ + try: + if os.path.splitext(metadata_path)[1] in ('.yml', '.yaml'): + load_func = yaml.safe_load + else: + load_func = json.load + with open(metadata_path, 'r') as in_file: + md_load = load_func(in_file) + if md_load is not None: + md_return = {'metadata': md_load} + else: + msg = 'Invalid JSON/YAML specified in metadata file "%s"' % metadata_path + logging.error(msg) + md_return = {'error': msg} + except Exception as ex: + msg = "Unable to load metadata file '%s'" % metadata_path + logging.error(msg) + logging.error('Exception caught: %s', str(ex)) + if logging.getLogger().level == logging.DEBUG: + logging.exception(msg) + md_return = {'error': msg} + + return md_return + + @staticmethod + def check_params_result_error(transformer_params: dict) -> Optional[dict]: + """Checks the transformer parameter results for an error + Arguments: + transformer_params: the dictionary to check for errors + Return: + An error dict if errors were found and None if not + Notes: + See handle_error() function + """ + if 'code' in transformer_params: + if 'error' in transformer_params: + error = transformer_params['error'] + else: + error = "Error returned from get_transformer_params with code: %s" % transformer_params['code'] + return __internal__.handle_error(-104, error) + + return None + + @staticmethod + def check_retrieve_results_error(transformer_retrieve: tuple) -> Optional[dict]: + """Checks the results of the transformer_class retrieving files + Arguments: + transformer_retrieve: the results of the retrieve + Return: + An error dict if errors were found and None if not + Notes: + See handle_error() function + """ + if not transformer_retrieve: + return None + + code = 0 + message = None + retrieve_len = len(transformer_retrieve) + if retrieve_len > 0: + code = transformer_retrieve[0] + if retrieve_len > 1: + message = transformer_retrieve[1] + else: + message = "Retrieving files returned a code of %s" % str(code) + + # Check for an error code + if code < 0: + return __internal__.handle_error(code, message) + + # Log the message if we get one returned to us + if retrieve_len > 1: + logging.info(transformer_retrieve[1]) + + return None + + @staticmethod + def check_metadata_needed() -> bool: + """Checks if metadata is required + Return: + Returns True if metadata is required (the default is that it's required), or False if not + """ + # Disable the following check since it's not a valid test here (METADATA_NEEDED is an optional variable) + # pylint: disable=no-member + + # If we have a variable defined, check the many ways of determining False + if hasattr(configuration, "METADATA_NEEDED"): + if not configuration.METADATA_NEEDED: + return False + if isinstance(configuration.METADATA_NEEDED, str): + if configuration.METADATA_NEEDED.lower().strip() == 'false': + return False + return True + + @staticmethod + def load_metadata_files(metadata_files: list) -> dict: + """Loads the specified metadata files + Arguments: + metadata_files: list of metadata files to load + Returns: + Returns a dict containing the loaded metadata as an array. If an error occurs, the dict + won't contain metadata but will contain an error message under an 'error' key. + """ + metadata = [] + result = {'metadata': metadata} + for metadata_file in metadata_files: + if not os.path.exists(metadata_file): + result = __internal__.handle_error(-2, "Unable to access metadata file '%s'" % metadata_file) + break + logging.info("Loading metadata from file: '%s'", metadata_file) + md_loaded = __internal__.load_metadata(metadata_file) + if 'metadata' in md_loaded: + metadata.append(md_loaded['metadata']) + else: + result = __internal__.handle_error(-3, md_loaded['error']) + break + + return result + + @staticmethod + def parse_continue_result(result) -> tuple: + """Parses the result of calling transformer.check_continue and returns + the code and/or message + Arguments: + result: the result from calling transformer.check_continue + Return: + A tuple containing the result code and result message. One or both of these + values in the tuple may be None + Notes: + A string parameter will always return a result code of None and message of None indicating + the caller needs to decide what to do. + An integer parameter will cause the result message value of None, the caller needs to decide + what an appropriate message is. + A parameter that's iterable with a length > 0 will have the first value as the result code and the + second value as the result message. No checks are made for type conformity. + If the parameter is something other than the above, an exception will most likely be thrown. + """ + result_code = None + result_message = None + + if isinstance(result, int): + result_code = result + elif not isinstance(result, str): + result_len = len(result) + if result_len > 0: + result_code = result[0] + if result_len > 1: + result_message = result[1] + + return (result_code, result_message) + + @staticmethod + def handle_check_continue(transformer_instance: transformer_class.Transformer, transformer_params: dict) -> dict: + """Handles calling the transformer.check_continue function + Arguments: + transformer_instance: instance of Transformer class + transformer_params: dictionary of parameters to pass to transform module functions + Return: + Returns the result of checking to continue operation + """ + result = {} + + if hasattr(transformer, 'check_continue'): + check_result = transformer.check_continue(transformer_instance, **transformer_params) + result_code, result_message = __internal__.parse_continue_result(check_result) + + if result_code: + result['code'] = result_code + if result_message: + result['message'] = result_message + else: + logging.debug("transformer module doesn't have a function named 'check_continue'") + + return result + + @staticmethod + def handle_retrieve_files(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) ->\ + Optional[dict]: + """Handles calling the transformer class to retrieve files + Arguments: + transformer_instance: the current transformer environment + args: the command line arguments + metadata: the loaded metadata + Return: + A dict containing error information if a problem occurs and None if no problems are found. + Note: + A side effect of this function is a information message logged if the transformer class instance does not have + a 'retrieve_files' function declared. + """ + if hasattr(transformer_instance, 'retrieve_files'): + transformer_retrieve = transformer_instance.retrieve_files(args, metadata) + retrieve_results = __internal__.check_retrieve_results_error(transformer_retrieve) + if retrieve_results: + return retrieve_results + else: + logging.info("Transformer class doesn't have function named 'retrieve_files'") + + return None + + @staticmethod + def perform_processing(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) -> dict: + """Makes the calls to perform the processing + Arguments: + transformer_instance: instance of transformer class + args: the command line arguments + metadata: the loaded metadata + Return: + Returns a dict containing the result of processing + """ + result = {} + + # Get the various types of parameters from the transformer instance + if hasattr(transformer_instance, 'get_transformer_params'): + transformer_params = transformer_instance.get_transformer_params(args, metadata) + if not isinstance(transformer_params, dict): + return __internal__.handle_error(-101, + "Invalid return from getting transformer parameters from transformer class instance") + + params_result = __internal__.check_params_result_error(transformer_params) + if params_result: + return params_result + else: + logging.info("Transformer class instance does not have get_transformer_params method") + transformer_params = {} + + # First check if the transformer thinks everything is in place + if hasattr(transformer, 'check_continue'): + result = __internal__.handle_check_continue(transformer_instance, transformer_params) + if 'code' in result and result['code'] < 0 and 'error' not in result: + result['error'] = "Unknown error returned from check_continue call" + else: + logging.info("Transformer module doesn't have a function named 'check_continue'") + + # Retrieve additional files if indicated by return code from the check + if 'error' not in result and 'code' in result and result['code'] == 0: + result = __internal__.handle_retrieve_files(transformer_instance, args, metadata) + + # Next make the call to perform the processing + if 'error' not in result: + if hasattr(transformer, 'perform_process'): + result = transformer.perform_process(transformer_instance, **transformer_params) + else: + logging.debug("Transformer module is missing function named 'perform_process'") + return __internal__.handle_error(-102, "Transformer perform_process interface is not available " + + "for processing data") + + return result + + @staticmethod + def handle_result(result: dict, result_types: str = None, result_file_path: str = None) -> dict: + """Handles the results of processing as dictated by the arguments passed in. + Arguments: + result: the dictionary of result information + result_types: optional, comma separated string containing one or more of: all, file, print + result_file_path: optional, location to place result file + Return: + Returns the result parameter + Notes: + If result_types is None then no actions are taken. If 'file' or 'all' is specified + in result_types and result_file_path is None or empty, writing to a file is skipped + """ + if not result_types is None: + type_parts = [one_type.strip() for one_type in result_types.split(',')] + if 'print' in type_parts or 'all' in type_parts: + print(json.dumps(result, indent=2)) + if 'file' in type_parts or 'all' in type_parts: + if result_file_path: + os.makedirs(os.path.dirname(result_file_path), exist_ok=True) + with open(result_file_path, 'w') as out_file: + json.dump(result, out_file, indent=2) + else: + logging.warning("Writing result to a file was requested but a file path wasn't provided.") + logging.warning(" Skipping writing to a file.") + + return result + +def add_parameters(parser: argparse.ArgumentParser, transformer_instance) -> None: + """Function to prepare and execute work unit + Arguments: + parser: an instance of argparse.ArgumentParser + """ + parser.add_argument('--debug', '-d', action='store_const', + default=logging.WARN, const=logging.DEBUG, + help='enable debug logging (default=WARN)') + + parser.add_argument('--info', '-i', action='store_const', + default=logging.WARN, const=logging.INFO, + help='enable info logging (default=WARN)') + + parser.add_argument('--result', nargs='?', default='all', + help='Direct the result of a run to one or more of (all is default): "all,file,print"') + + parser.add_argument('--metadata', type=str, action='append', help='The path to the source metadata') + + parser.add_argument('--working_space', type=str, help='the folder to use use as a workspace and ' + + 'for storing results') + + # Let the transformer class add parameters + if hasattr(transformer_instance, 'add_parameters'): + transformer_instance.add_parameters(parser) + + # Check if the transformer has a function defined to extend command line arguments + if hasattr(transformer, 'add_parameters'): + transformer.add_parameters(parser) + + # Assume the rest of the arguments are the files + parser.add_argument('file_list', nargs=argparse.REMAINDER, help='additional files for transformer') + +def do_work(parser: argparse.ArgumentParser, **kwargs) -> dict: + """Function to prepare and execute work unit + Arguments: + parser: an instance of argparse.ArgumentParser + kwargs: keyword args + """ + result = {} + + # Create an instance of the transformer + transformer_instance = transformer_class.Transformer(**kwargs) + if not transformer_instance: + result = __internal__.handle_error(-100, "Unable to create transformer class instance for processing") + return __internal__.handle_result(result, None, None) + + add_parameters(parser, transformer_instance) + args = parser.parse_args() + + # start logging system + logging.getLogger().setLevel(args.debug if args.debug == logging.DEBUG else args.info) + + # Check that we have mandatory metadata + if not args.metadata and __internal__.check_metadata_needed(): + result = __internal__.handle_error(-1, "No metadata paths were specified.") + else: + md_results = __internal__.load_metadata_files(args.metadata) + if 'metadata' in md_results: + result = __internal__.perform_processing(transformer_instance, args, md_results['metadata']) + else: + result = __internal__.handle_error(-3, md_results['error']) + + if args.working_space: + result_path = os.path.join(args.working_space, 'result.json') + else: + result_path = None + + __internal__.handle_result(result, args.result, result_path) + return result + +if __name__ == "__main__": + try: + PARSER = argparse.ArgumentParser(description=configuration.TRANSFORMER_DESCRIPTION) + do_work(PARSER) + except Exception as ex: + logging.error("Top level exception handler caught an exception: %s", str(ex)) + raise diff --git a/transformer.py b/transformer.py index 66aedee..8729bea 100644 --- a/transformer.py +++ b/transformer.py @@ -7,13 +7,10 @@ import numpy as np import cv2 -from osgeo import gdal +from osgeo import gdal, osr # from PIL import Image Used by code that's getting deprecated from skimage import morphology -from terrautils.formats import create_geotiff as tr_create_geotiff, \ - compress_geotiff as tr_compress_geotiff - import configuration import transformer_class @@ -29,6 +26,132 @@ def __init__(self): """Performs initialization of class instance """ + @staticmethod + def prepare_metadata_for_geotiff(extractor_info=None, terra_md=None): + """Create geotiff-embedded metadata from extractor_info and terraref metadata pieces. + + Keyword arguments: + extractor_info -- details about extractor if applicable + system_md -- cleaned TERRA-REF metadata + """ + extra_metadata = {} + + if (terra_md != None): + extra_metadata["datetime"] = str(terra_md["gantry_variable_metadata"]["datetime"]) + extra_metadata["sensor_id"] = str(terra_md["sensor_fixed_metadata"]["sensor_id"]) + extra_metadata["sensor_url"] = str(terra_md["sensor_fixed_metadata"]["url"]) + experiment_names = [] + for e in terra_md["experiment_metadata"]: + experiment_names.append(e["name"]) + terra_md["experiment_name"] = ", ".join(experiment_names) + + if (extractor_info != None): + extra_metadata["extractor_name"] = str(extractor_info.get("name", "")) + extra_metadata["extractor_version"] = str(extractor_info.get("version", "")) + extra_metadata["extractor_author"] = str(extractor_info.get("author", "")) + extra_metadata["extractor_description"] = str(extractor_info.get("description", "")) + if "repository" in extractor_info and "repUrl" in extractor_info["repository"]: + extra_metadata["extractor_repo"] = str(extractor_info["repository"]["repUrl"]) + else: + extra_metadata["extractor_repo"] = "" + + return extra_metadata + + @staticmethod + def create_geotiff(pixels, gps_bounds, out_path, nodata=-99, asfloat=False, extractor_info=None, system_md=None, + extra_metadata=None, compress=False): + """Generate output GeoTIFF file given a numpy pixel array and GPS boundary. + + Keyword arguments: + pixels -- numpy array of pixel values. + if 2-dimensional array, a single-band GeoTIFF will be created. + if 3-dimensional array, a band will be created for each Z dimension. + gps_bounds -- tuple of GeoTIFF coordinates as ( lat (y) min, lat (y) max, + long (x) min, long (x) max) + out_path -- path to GeoTIFF to be created + nodata -- NoDataValue to be assigned to raster bands; set to None to ignore + float -- whether to use GDT_Float32 data type instead of GDT_Byte (e.g. for decimal numbers) + extractor_info -- details about extractor if applicable + system_md -- cleaned TERRA-REF metadata + extra_metadata -- any metadata to be embedded in geotiff; supersedes extractor_info and system_md + """ + dimensions = np.shape(pixels) + if len(dimensions) == 2: + nrows, ncols = dimensions + channels = 1 + else: + nrows, ncols, channels = dimensions + + geotransform = ( + gps_bounds[2], # upper-left x + (gps_bounds[3] - gps_bounds[2]) / float(ncols), # W-E pixel resolution + 0, # rotation (0 = North is up) + gps_bounds[1], # upper-left y + 0, # rotation (0 = North is up) + -((gps_bounds[1] - gps_bounds[0]) / float(nrows)) # N-S pixel resolution + ) + + # Create output GeoTIFF and set coordinates & projection + if asfloat: + dtype = gdal.GDT_Float32 + else: + dtype = gdal.GDT_Byte + + if compress: + output_raster = gdal.GetDriverByName('GTiff') \ + .Create(out_path, ncols, nrows, channels, dtype, ['COMPRESS=LZW']) + else: + output_raster = gdal.GetDriverByName('GTiff') \ + .Create(out_path, ncols, nrows, channels, dtype) + + output_raster.SetGeoTransform(geotransform) + srs = osr.SpatialReference() + srs.ImportFromEPSG(4326) # google mercator + output_raster.SetProjection(srs.ExportToWkt()) + + if not extra_metadata: + extra_metadata = __internal__.prepare_metadata_for_geotiff(extractor_info, system_md) + + output_raster.SetMetadata(extra_metadata) + + if channels == 3: + # typically 3 channels = RGB channels + # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels) + output_raster.GetRasterBand(1).WriteArray(pixels[:, :, 0].astype('uint8')) + output_raster.GetRasterBand(1).SetColorInterpretation(gdal.GCI_RedBand) + output_raster.GetRasterBand(1).FlushCache() + if nodata: + output_raster.GetRasterBand(1).SetNoDataValue(nodata) + + output_raster.GetRasterBand(2).WriteArray(pixels[:, :, 1].astype('uint8')) + output_raster.GetRasterBand(2).SetColorInterpretation(gdal.GCI_GreenBand) + output_raster.GetRasterBand(2).FlushCache() + if nodata: + output_raster.GetRasterBand(2).SetNoDataValue(nodata) + + output_raster.GetRasterBand(3).WriteArray(pixels[:, :, 2].astype('uint8')) + output_raster.GetRasterBand(3).SetColorInterpretation(gdal.GCI_BlueBand) + output_raster.GetRasterBand(3).FlushCache() + if nodata: + output_raster.GetRasterBand(3).SetNoDataValue(nodata) + + elif channels > 1: + # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels) + for chan in range(channels): + band = chan + 1 + output_raster.GetRasterBand(band).WriteArray(pixels[:, :, chan].astype('uint8')) + output_raster.GetRasterBand(band).FlushCache() + if nodata: + output_raster.GetRasterBand(band).SetNoDataValue(nodata) + else: + # single channel image, e.g. temperature + output_raster.GetRasterBand(1).WriteArray(pixels) + output_raster.GetRasterBand(1).FlushCache() + if nodata: + output_raster.GetRasterBand(1).SetNoDataValue(nodata) + + output_raster = None + # @staticmethod # def get_image_quality(imgfile: str) -> np.ndarray: # """Computes and returns the image score for the image file @@ -442,9 +565,8 @@ def perform_process(transformer: transformer_class.Transformer, check_md: dict, transformer_info = transformer.generate_transformer_md() - tr_create_geotiff(mask_rgb, bounds, rgb_mask_tif, None, False, - transformer_info, check_md['context_md']) - tr_compress_geotiff(rgb_mask_tif) + __internal__.create_geotiff(mask_rgb, bounds, rgb_mask_tif, None, False, + transformer_info, check_md['context_md'], compress=True) # Remove any temporary file if mask_source != one_file: diff --git a/transformer_class.py b/transformer_class.py new file mode 100644 index 0000000..ece753c --- /dev/null +++ b/transformer_class.py @@ -0,0 +1,311 @@ +"""Class instance for Transformer +""" + +import argparse +import datetime +import logging +from osgeo import gdal, osr +from numpy import nan +import piexif +from typing import Optional + +import configuration + +# EXIF tags to look for +EXIF_ORIGIN_TIMESTAMP = 36867 # Capture timestamp +EXIF_TIMESTAMP_OFFSET = 36881 # Timestamp UTC offset (general) +EXIF_ORIGIN_TIMESTAMP_OFFSET = 36881 # Capture timestamp UTC offset + + +class __internal__(): + """Class containing functions for this file only + """ + def __init__(self): + """Perform class level initialization + """ + + @staticmethod + def image_get_geobounds(filename: str) -> list: + """Uses gdal functionality to retrieve recilinear boundaries from the file + + Args: + filename(str): path of the file to get the boundaries from + + Returns: + The upper-left and calculated lower-right boundaries of the image in a list upon success. + The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan + in each position is returned if the boundaries can't be determined + """ + try: + src = gdal.Open(filename) + ulx, xres, _, uly, _, yres = src.GetGeoTransform() + lrx = ulx + (src.RasterXSize * xres) + lry = uly + (src.RasterYSize * yres) + + min_y = min(uly, lry) + max_y = max(uly, lry) + min_x = min(ulx, lrx) + max_x = max(ulx, lrx) + + return [min_y, max_y, min_x, max_x] + except Exception as ex: + logging.info("[image_get_geobounds] Exception caught: %s", str(ex)) + if logging.getLogger().level == logging.DEBUG: + logging.exception("[image_get_geobounds] Exception") + + return [nan, nan, nan, nan] + + @staticmethod + def get_epsg(filename: str) -> Optional[str]: + """Returns the EPSG of the georeferenced image file + Args: + filename(str): path of the file to retrieve the EPSG code from + Return: + Returns the found EPSG code, or None if it's not found or an error ocurred + """ + logger = logging.getLogger(__name__) + + try: + src = gdal.Open(filename) + + proj = osr.SpatialReference(wkt=src.GetProjection()) + + return proj.GetAttrValue('AUTHORITY', 1) + except Exception as ex: + logger.warning("[get_epsg] Exception caught: %s", str(ex)) + if logging.getLogger().level == logging.DEBUG: + logging.exception("[get_epsg] Exception") + + return None + + @staticmethod + def exif_tags_to_timestamp(exif_tags): + """Looks up the origin timestamp and a timestamp offset in the exit tags and returns + a datetime object + Args: + exif_tags(dict): The exif tags to search for timestamp information + Return: + Returns the origin timestamp when found. The return timestamp is adjusted for UTF if + an offset is found. None is returned if a valid timestamp isn't found. + """ + cur_stamp, cur_offset = (None, None) + + def convert_and_clean_tag(value): + """Internal helper function for handling EXIF tag values. Tests for an empty string after + stripping colons, '+', '-', and whitespace [the spec is unclear if a +/- is needed when + the timestamp offset is unknown (and spaces are used)]. + Args: + value(bytes or str): The tag value + Return: + Returns the cleaned up, and converted from bytes, string. Or None if the value is empty + after stripping above characters and whitespace. + """ + if not value: + return None + + # Convert bytes to string + if isinstance(value, bytes): + value = value.decode('UTF-8').strip() + else: + value = value.strip() + + # Check for an empty string after stripping colons + if value: + if not value.replace(":", "").replace("+:", "").replace("-", "").strip(): + value = None + + return None if not value else value + + # Process the EXIF data + if EXIF_ORIGIN_TIMESTAMP in exif_tags: + cur_stamp = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP]) + if not cur_stamp: + return None + + if EXIF_ORIGIN_TIMESTAMP_OFFSET in exif_tags: + cur_offset = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP_OFFSET]) + if not cur_offset and EXIF_TIMESTAMP_OFFSET in exif_tags: + cur_offset = convert_and_clean_tag(exif_tags[EXIF_TIMESTAMP_OFFSET]) + + # Format the string to a timestamp and return the result + try: + if not cur_offset: + cur_ts = datetime.datetime.fromisoformat(cur_stamp) + else: + cur_offset = cur_offset.replace(":", "") + cur_ts = datetime.datetime.fromisoformat(cur_stamp + cur_offset) + except Exception as ex: + cur_ts = None + logging.debug("Exception caught converting EXIF tag to timestamp: %s", str(ex)) + + return cur_ts + + @staticmethod + def get_first_timestamp(file_path: str, timestamp: str = None) -> str: + """Looks for a timestamp in the specified file and returns + the earliest timestamp (when compared to the timestamp parameter) + Arguments: + file_path: the path to the file to check + timestamp: the timestamp to compare against (when specified) + Return: + The earliest found timestamp + """ + first_stamp = datetime.datetime.fromisoformat(timestamp) if timestamp else None + try: + tags_dict = piexif.load(file_path) + if tags_dict and "Exif" in tags_dict: + cur_stamp = __internal__.exif_tags_to_timestamp(tags_dict["Exif"]) + if cur_stamp: + first_stamp = cur_stamp if first_stamp is None or cur_stamp < first_stamp else first_stamp + except Exception as ex: + logging.debug("Exception caught getting timestamp from file: %s", file_path) + logging.debug(" %s", str(ex)) + + if first_stamp: + return first_stamp.isoformat() + + return timestamp + + +class Transformer(): + """Generic class for supporting transformers + """ + + def __init__(self, **kwargs): + """Performs initialization of class instance + Arguments: + kwargs: additional parameters passed in to Transformer + """ + # pylint: disable=unused-argument + self.sensor = None + self.args = None + + @property + def default_epsg(self) -> int: + """Returns the current working EPSG code + """ + return 4326 + + @property + def supported_image_file_exts(self): + """Returns the list of supported image file extension strings (in lower case) + """ + return ['tif', 'tiff', 'jpg'] + + def get_image_file_epsg(self, source_path: str) -> str: + """Returns the EPSG of the georeferenced image file + Arguments: + source_path: the path to the image to load the EPSG code from + Return: + Returns the EPSG code loaded from the file. None is returned if there is a problem or the file + doesn't have an EPSG code + """ + # pylint: disable=no-self-use + return __internal__.get_epsg(source_path) + + def get_image_file_geobounds(self, source_path: str) -> list: + """Uses gdal functionality to retrieve rectilinear boundaries from the file + Args: + source_path(str): path of the file to get the boundaries from + Returns: + The upper-left and calculated lower-right boundaries of the image in a list upon success. + The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan + is returned if the boundaries can't be determined + """ + # pylint: disable=no-self-use + return __internal__.image_get_geobounds(source_path) + + def generate_transformer_md(self) -> dict: + """Generates metadata about this transformer + Returns: + Returns the transformer metadata + """ + # pylint: disable=no-self-use + return { + 'version': configuration.TRANSFORMER_VERSION, + 'name': configuration.TRANSFORMER_NAME, + 'author': configuration.AUTHOR_NAME, + 'description': configuration.TRANSFORMER_DESCRIPTION, + 'repository': {'repUrl': configuration.REPOSITORY} + } + + def add_parameters(self, parser: argparse.ArgumentParser) -> None: + """Adds processing parameters to existing parameters + Arguments: + parser: instance of argparse + """ + # pylint: disable=no-self-use + parser.epilog = configuration.TRANSFORMER_NAME + ' version ' + configuration.TRANSFORMER_VERSION + \ + ' author ' + configuration.AUTHOR_NAME + ' ' + configuration.AUTHOR_EMAIL + + def get_transformer_params(self, args: argparse.Namespace, metadata: list) -> dict: + """Returns a parameter list for processing data + Arguments: + args: result of calling argparse.parse_args + metadata: the loaded metadata + """ + # Disabling this warning to keep code readable + # pylint: disable=too-many-branches + self.args = args + + timestamp, season_name, experiment_name = None, None, None + parsed_metadata = [] + transformer_md = [] + + # Loop through the metadata + for one_metadata in metadata: + # Determine if we're using JSONLD + if 'content' in one_metadata: + parse_md = one_metadata['content'] + else: + parse_md = one_metadata + # Check for legacy 'pipeline' key + if 'pipeline' in parse_md: + parse_md = parse_md['pipeline'] + parsed_metadata.append(parse_md) + + # Get the season, experiment, etc information + if 'observationTimeStamp' in parse_md: + timestamp = parse_md['observationTimeStamp'] + if 'season' in parse_md: + season_name = parse_md['season'] + if 'studyName' in parse_md: + experiment_name = parse_md['studyName'] + + # Check for transformer specific metadata + if configuration.TRANSFORMER_NAME in parse_md: + if isinstance(parse_md[configuration.TRANSFORMER_NAME], list): + transformer_md.extend(parse_md[configuration.TRANSFORMER_NAME]) + else: + transformer_md.append(parse_md[configuration.TRANSFORMER_NAME]) + # Get the list of files, if there are some and find the earliest timestamp if a timestamp + # hasn't been specified yet + file_list = [] + working_timestamp = timestamp + if args.file_list: + for one_file in args.file_list: + # Filter out arguments that are obviously not files + if not one_file.startswith('-'): + file_list.append(one_file) + # Only bother to get a timestamp if we don't have one specified + if timestamp is None: + working_timestamp = __internal__.get_first_timestamp(one_file, working_timestamp) + if timestamp is None and working_timestamp is not None: + timestamp = working_timestamp + + # Prepare our parameters + check_md = {'timestamp': timestamp, + 'season': season_name, + 'experiment': experiment_name, + 'container_name': None, + 'target_container_name': None, + 'trigger_name': None, + 'context_md': None, + 'working_folder': args.working_space, + 'list_files': lambda: file_list + } + + return {'check_md': check_md, + 'transformer_md': transformer_md, + 'full_md': parsed_metadata + } From 18c2ce3c58d7396d55ea60705f7e9dd5cb5decda Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Thu, 11 Jun 2020 11:29:25 -0700 Subject: [PATCH 34/42] Changing error message --- .github/workflows/pylint_check.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pylint_check.yaml b/.github/workflows/pylint_check.yaml index 1774738..b5c4524 100644 --- a/.github/workflows/pylint_check.yaml +++ b/.github/workflows/pylint_check.yaml @@ -68,7 +68,7 @@ jobs: id: install-python-reqs - name: Run action pylint script shell: bash - run: '[ -s ".github/workflows/action_pylint.sh" ] && (chmod +x ".github/workflows/action_pylint.sh" && ./.github/workflows/action_pylint.sh) || (echo "Not running special action script - empty or not found")' + run: '[ -s ".github/workflows/action_pylint.sh" ] && (chmod +x ".github/workflows/action_pylint.sh" && ./.github/workflows/action_pylint.sh) || (echo "Error running shell script")' id: run-special-action-script - name: Fetching pylint.rc file run: wget https://raw.githubusercontent.com/AgPipeline/Organization-info/master/pylint.rc From 1a27b0eb8b8e47a397befefea5162603ca30020b Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Thu, 25 Jun 2020 16:11:41 -0700 Subject: [PATCH 35/42] Changes to using agpypeline library --- Dockerfile | 10 +- configuration.py | 41 +-- entrypoint.py | 409 ----------------------------- soilmask.py | 425 ++++++++++++++++++++++++++++++ transformer.py | 596 ------------------------------------------- transformer_class.py | 311 ---------------------- 6 files changed, 456 insertions(+), 1336 deletions(-) delete mode 100755 entrypoint.py create mode 100644 soilmask.py delete mode 100644 transformer.py delete mode 100644 transformer_class.py diff --git a/Dockerfile b/Dockerfile index 52fbf01..2ee935b 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,6 +1,7 @@ -FROM FROM agdrone/drone-base-image:1.2 +FROM agpypeline LABEL maintainer="Chris Schnaufer " +# Start installing things COPY requirements.txt packages.txt /home/extractor/ USER root @@ -26,5 +27,10 @@ RUN [ -s /home/extractor/requirements.txt ] && \ rm /home/extractor/requirements.txt) USER extractor +COPY configuration.py soilmask.py /home/extractor/ -COPY configuration.py transformer.py /home/extractor/ +USER root +RUN chmod a+x /home/extractor/soilmask.py + +USER extractor +ENTRYPOINT ["/home/extractor/soilmask.py"] \ No newline at end of file diff --git a/configuration.py b/configuration.py index ba4e38b..7ed476c 100644 --- a/configuration.py +++ b/configuration.py @@ -1,29 +1,34 @@ """Contains transformer configuration information """ +from agpypeline.configuration import Configuration -# The version number of the transformer -TRANSFORMER_VERSION = '2.0' +class ConfigurationSoilmask(Configuration): + # Silence this error until we have public methods + # pylint: disable=too-few-public-methods -# The transformer description -TRANSFORMER_DESCRIPTION = 'Stereo RGB Image Enhancement & Masking' + # The version number of the transformer + transformer_version = '2.0' -# Short name of the transformer -TRANSFORMER_NAME = 'terra.stereo-rgb.rgbmask' + # The transformer description + transformer_description = 'Stereo RGB Image Enhancement & Masking' -# The name of the author of the extractor -AUTHOR_NAME = 'Chris Schnaufer' + # Short name of the transformer + transformer_name = 'terra.stereo-rgb.rgbmask' -# The email of the author of the extractor -AUTHOR_EMAIL = 'schnaufer@email.arizona.edu' + # The name of the author of the extractor + author_name = 'Chris Schnaufer' -# Reposity URI of where the source code lives -REPOSITORY = 'https://github.com/Chris-Schnaufer/rgbmask.git' + # The email of the author of the extractor + author_email = 'schnaufer@email.arizona.edu' -# Contributors to this transformer -CONTRUBUTORS = ['Max Burnette', 'Zongyang Li', 'Todd Nicholson'] + # Reposity URI of where the source code lives + repository = 'https://github.com/Chris-Schnaufer/rgbmask.git' -# The sensor associated with the transformer -TRANSFORMER_SENSOR = 'stereoTop' + # Contributors to this transformer + contrubutors = ['Max Burnette', 'Zongyang Li', 'Todd Nicholson'] -# The transformer type (eg: 'rgbmask', 'plotclipper') -TRANSFORMER_TYPE = 'rgb_mask' + # The sensor associated with the transformer + transformer_sensor = 'stereoTop' + + # The transformer type (eg: 'rgbmask', 'plotclipper') + transformer_type = 'rgb_mask' diff --git a/entrypoint.py b/entrypoint.py deleted file mode 100755 index 2db27cb..0000000 --- a/entrypoint.py +++ /dev/null @@ -1,409 +0,0 @@ -#!/usr/bin/env python3 -"""Base entry point for Agriculture Pipeline transformer -""" - -import argparse -import os -import json -import logging -from typing import Optional -import yaml - -import transformer_class - -# From derived images -import configuration -import transformer - -class __internal__(): - """Class for functions intended for internal use only for this file - """ - def __init__(self): - """Performs initialization of class instance - """ - - @staticmethod - def handle_error(code: int, message: str) -> dict: - """Handles logging and return values when an error occurs. Implies processing - will stop. - Arguments: - code: return code related to the error - message: the message string of the error - Return: - Returns a dict with the code and message - """ - if code is None: - logging.warning("An error has occurred without a return code specified, setting default return code") - code = -1 - if not message: - logging.warning("An error has occurred without a message, setting default message") - message = "An error has occurred with error code (%s)" % str(code) - - logging.error(message) - logging.error("Stopping processing") - - result = {'error': message, 'code': code} - - return result - - @staticmethod - def load_metadata(metadata_path: str) -> dict: - """Loads the metadata from the specified path - Arguments: - metadata_path: path to the metadata file - Return: - Returns a dict containing the loaded metadata. If an error occurs, the dict - won't contain metadata but will contain an error message under an 'error' key. - """ - try: - if os.path.splitext(metadata_path)[1] in ('.yml', '.yaml'): - load_func = yaml.safe_load - else: - load_func = json.load - with open(metadata_path, 'r') as in_file: - md_load = load_func(in_file) - if md_load is not None: - md_return = {'metadata': md_load} - else: - msg = 'Invalid JSON/YAML specified in metadata file "%s"' % metadata_path - logging.error(msg) - md_return = {'error': msg} - except Exception as ex: - msg = "Unable to load metadata file '%s'" % metadata_path - logging.error(msg) - logging.error('Exception caught: %s', str(ex)) - if logging.getLogger().level == logging.DEBUG: - logging.exception(msg) - md_return = {'error': msg} - - return md_return - - @staticmethod - def check_params_result_error(transformer_params: dict) -> Optional[dict]: - """Checks the transformer parameter results for an error - Arguments: - transformer_params: the dictionary to check for errors - Return: - An error dict if errors were found and None if not - Notes: - See handle_error() function - """ - if 'code' in transformer_params: - if 'error' in transformer_params: - error = transformer_params['error'] - else: - error = "Error returned from get_transformer_params with code: %s" % transformer_params['code'] - return __internal__.handle_error(-104, error) - - return None - - @staticmethod - def check_retrieve_results_error(transformer_retrieve: tuple) -> Optional[dict]: - """Checks the results of the transformer_class retrieving files - Arguments: - transformer_retrieve: the results of the retrieve - Return: - An error dict if errors were found and None if not - Notes: - See handle_error() function - """ - if not transformer_retrieve: - return None - - code = 0 - message = None - retrieve_len = len(transformer_retrieve) - if retrieve_len > 0: - code = transformer_retrieve[0] - if retrieve_len > 1: - message = transformer_retrieve[1] - else: - message = "Retrieving files returned a code of %s" % str(code) - - # Check for an error code - if code < 0: - return __internal__.handle_error(code, message) - - # Log the message if we get one returned to us - if retrieve_len > 1: - logging.info(transformer_retrieve[1]) - - return None - - @staticmethod - def check_metadata_needed() -> bool: - """Checks if metadata is required - Return: - Returns True if metadata is required (the default is that it's required), or False if not - """ - # Disable the following check since it's not a valid test here (METADATA_NEEDED is an optional variable) - # pylint: disable=no-member - - # If we have a variable defined, check the many ways of determining False - if hasattr(configuration, "METADATA_NEEDED"): - if not configuration.METADATA_NEEDED: - return False - if isinstance(configuration.METADATA_NEEDED, str): - if configuration.METADATA_NEEDED.lower().strip() == 'false': - return False - return True - - @staticmethod - def load_metadata_files(metadata_files: list) -> dict: - """Loads the specified metadata files - Arguments: - metadata_files: list of metadata files to load - Returns: - Returns a dict containing the loaded metadata as an array. If an error occurs, the dict - won't contain metadata but will contain an error message under an 'error' key. - """ - metadata = [] - result = {'metadata': metadata} - for metadata_file in metadata_files: - if not os.path.exists(metadata_file): - result = __internal__.handle_error(-2, "Unable to access metadata file '%s'" % metadata_file) - break - logging.info("Loading metadata from file: '%s'", metadata_file) - md_loaded = __internal__.load_metadata(metadata_file) - if 'metadata' in md_loaded: - metadata.append(md_loaded['metadata']) - else: - result = __internal__.handle_error(-3, md_loaded['error']) - break - - return result - - @staticmethod - def parse_continue_result(result) -> tuple: - """Parses the result of calling transformer.check_continue and returns - the code and/or message - Arguments: - result: the result from calling transformer.check_continue - Return: - A tuple containing the result code and result message. One or both of these - values in the tuple may be None - Notes: - A string parameter will always return a result code of None and message of None indicating - the caller needs to decide what to do. - An integer parameter will cause the result message value of None, the caller needs to decide - what an appropriate message is. - A parameter that's iterable with a length > 0 will have the first value as the result code and the - second value as the result message. No checks are made for type conformity. - If the parameter is something other than the above, an exception will most likely be thrown. - """ - result_code = None - result_message = None - - if isinstance(result, int): - result_code = result - elif not isinstance(result, str): - result_len = len(result) - if result_len > 0: - result_code = result[0] - if result_len > 1: - result_message = result[1] - - return (result_code, result_message) - - @staticmethod - def handle_check_continue(transformer_instance: transformer_class.Transformer, transformer_params: dict) -> dict: - """Handles calling the transformer.check_continue function - Arguments: - transformer_instance: instance of Transformer class - transformer_params: dictionary of parameters to pass to transform module functions - Return: - Returns the result of checking to continue operation - """ - result = {} - - if hasattr(transformer, 'check_continue'): - check_result = transformer.check_continue(transformer_instance, **transformer_params) - result_code, result_message = __internal__.parse_continue_result(check_result) - - if result_code: - result['code'] = result_code - if result_message: - result['message'] = result_message - else: - logging.debug("transformer module doesn't have a function named 'check_continue'") - - return result - - @staticmethod - def handle_retrieve_files(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) ->\ - Optional[dict]: - """Handles calling the transformer class to retrieve files - Arguments: - transformer_instance: the current transformer environment - args: the command line arguments - metadata: the loaded metadata - Return: - A dict containing error information if a problem occurs and None if no problems are found. - Note: - A side effect of this function is a information message logged if the transformer class instance does not have - a 'retrieve_files' function declared. - """ - if hasattr(transformer_instance, 'retrieve_files'): - transformer_retrieve = transformer_instance.retrieve_files(args, metadata) - retrieve_results = __internal__.check_retrieve_results_error(transformer_retrieve) - if retrieve_results: - return retrieve_results - else: - logging.info("Transformer class doesn't have function named 'retrieve_files'") - - return None - - @staticmethod - def perform_processing(transformer_instance: transformer_class.Transformer, args: argparse.Namespace, metadata: dict) -> dict: - """Makes the calls to perform the processing - Arguments: - transformer_instance: instance of transformer class - args: the command line arguments - metadata: the loaded metadata - Return: - Returns a dict containing the result of processing - """ - result = {} - - # Get the various types of parameters from the transformer instance - if hasattr(transformer_instance, 'get_transformer_params'): - transformer_params = transformer_instance.get_transformer_params(args, metadata) - if not isinstance(transformer_params, dict): - return __internal__.handle_error(-101, - "Invalid return from getting transformer parameters from transformer class instance") - - params_result = __internal__.check_params_result_error(transformer_params) - if params_result: - return params_result - else: - logging.info("Transformer class instance does not have get_transformer_params method") - transformer_params = {} - - # First check if the transformer thinks everything is in place - if hasattr(transformer, 'check_continue'): - result = __internal__.handle_check_continue(transformer_instance, transformer_params) - if 'code' in result and result['code'] < 0 and 'error' not in result: - result['error'] = "Unknown error returned from check_continue call" - else: - logging.info("Transformer module doesn't have a function named 'check_continue'") - - # Retrieve additional files if indicated by return code from the check - if 'error' not in result and 'code' in result and result['code'] == 0: - result = __internal__.handle_retrieve_files(transformer_instance, args, metadata) - - # Next make the call to perform the processing - if 'error' not in result: - if hasattr(transformer, 'perform_process'): - result = transformer.perform_process(transformer_instance, **transformer_params) - else: - logging.debug("Transformer module is missing function named 'perform_process'") - return __internal__.handle_error(-102, "Transformer perform_process interface is not available " + - "for processing data") - - return result - - @staticmethod - def handle_result(result: dict, result_types: str = None, result_file_path: str = None) -> dict: - """Handles the results of processing as dictated by the arguments passed in. - Arguments: - result: the dictionary of result information - result_types: optional, comma separated string containing one or more of: all, file, print - result_file_path: optional, location to place result file - Return: - Returns the result parameter - Notes: - If result_types is None then no actions are taken. If 'file' or 'all' is specified - in result_types and result_file_path is None or empty, writing to a file is skipped - """ - if not result_types is None: - type_parts = [one_type.strip() for one_type in result_types.split(',')] - if 'print' in type_parts or 'all' in type_parts: - print(json.dumps(result, indent=2)) - if 'file' in type_parts or 'all' in type_parts: - if result_file_path: - os.makedirs(os.path.dirname(result_file_path), exist_ok=True) - with open(result_file_path, 'w') as out_file: - json.dump(result, out_file, indent=2) - else: - logging.warning("Writing result to a file was requested but a file path wasn't provided.") - logging.warning(" Skipping writing to a file.") - - return result - -def add_parameters(parser: argparse.ArgumentParser, transformer_instance) -> None: - """Function to prepare and execute work unit - Arguments: - parser: an instance of argparse.ArgumentParser - """ - parser.add_argument('--debug', '-d', action='store_const', - default=logging.WARN, const=logging.DEBUG, - help='enable debug logging (default=WARN)') - - parser.add_argument('--info', '-i', action='store_const', - default=logging.WARN, const=logging.INFO, - help='enable info logging (default=WARN)') - - parser.add_argument('--result', nargs='?', default='all', - help='Direct the result of a run to one or more of (all is default): "all,file,print"') - - parser.add_argument('--metadata', type=str, action='append', help='The path to the source metadata') - - parser.add_argument('--working_space', type=str, help='the folder to use use as a workspace and ' + - 'for storing results') - - # Let the transformer class add parameters - if hasattr(transformer_instance, 'add_parameters'): - transformer_instance.add_parameters(parser) - - # Check if the transformer has a function defined to extend command line arguments - if hasattr(transformer, 'add_parameters'): - transformer.add_parameters(parser) - - # Assume the rest of the arguments are the files - parser.add_argument('file_list', nargs=argparse.REMAINDER, help='additional files for transformer') - -def do_work(parser: argparse.ArgumentParser, **kwargs) -> dict: - """Function to prepare and execute work unit - Arguments: - parser: an instance of argparse.ArgumentParser - kwargs: keyword args - """ - result = {} - - # Create an instance of the transformer - transformer_instance = transformer_class.Transformer(**kwargs) - if not transformer_instance: - result = __internal__.handle_error(-100, "Unable to create transformer class instance for processing") - return __internal__.handle_result(result, None, None) - - add_parameters(parser, transformer_instance) - args = parser.parse_args() - - # start logging system - logging.getLogger().setLevel(args.debug if args.debug == logging.DEBUG else args.info) - - # Check that we have mandatory metadata - if not args.metadata and __internal__.check_metadata_needed(): - result = __internal__.handle_error(-1, "No metadata paths were specified.") - else: - md_results = __internal__.load_metadata_files(args.metadata) - if 'metadata' in md_results: - result = __internal__.perform_processing(transformer_instance, args, md_results['metadata']) - else: - result = __internal__.handle_error(-3, md_results['error']) - - if args.working_space: - result_path = os.path.join(args.working_space, 'result.json') - else: - result_path = None - - __internal__.handle_result(result, args.result, result_path) - return result - -if __name__ == "__main__": - try: - PARSER = argparse.ArgumentParser(description=configuration.TRANSFORMER_DESCRIPTION) - do_work(PARSER) - except Exception as ex: - logging.error("Top level exception handler caught an exception: %s", str(ex)) - raise diff --git a/soilmask.py b/soilmask.py new file mode 100644 index 0000000..c6633d6 --- /dev/null +++ b/soilmask.py @@ -0,0 +1,425 @@ +#!/usr/bin/env python3 +"""Testing instance of transformer +""" + +import logging +import os +import numpy as np +from agpypeline import entrypoint, algorithm, geoimage +from agpypeline.environment import Environment +import cv2 + +from osgeo import gdal +# from PIL import Image Used by code that's getting deprecated +from skimage import morphology + +from configuration import ConfigurationSoilmask + +SATURATE_THRESHOLD = 245 +MAX_PIXEL_VAL = 255 +SMALL_AREA_THRESHOLD = 200 + + +class __internal__: + """Class for functions intended for internal use only for this file + """ + def __init__(self): + """Performs initialization of class instance + """ + + @staticmethod + def prepare_metadata_for_geotiff(transformer_info: dict = None) -> dict: + """Create geotiff-embedable metadata from extractor_info and other metadata pieces. + Arguments: + transformer_info: details about the transformer + Return: + A dict containing information to save with an image + """ + extra_metadata = {} + + if transformer_info: + extra_metadata["transformer_name"] = str(transformer_info.get("name", "")) + extra_metadata["transformer_version"] = str(transformer_info.get("version", "")) + extra_metadata["transformer_author"] = str(transformer_info.get("author", "")) + extra_metadata["transformer_description"] = str(transformer_info.get("description", "")) + if "repository" in transformer_info and "repUrl" in transformer_info["repository"]: + extra_metadata["transformer_repo"] = str(transformer_info["repository"]["repUrl"]) + else: + extra_metadata["transformer_repo"] = "" + + return extra_metadata + + @staticmethod + def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: + """Generates an image with plants masked in. + Arguments: + color_img: RGB image to mask + kernel_size: masking kernel size + Return: + An RGB image with plants masked in + """ + r_channel = color_img[:, :, 2] + g_channel = color_img[:, :, 1] + b_channel = color_img[:, :, 0] + + sub_img = (g_channel.astype('int') - r_channel.astype('int') - 0) > 0 # normal: -2 + + mask = np.zeros_like(b_channel) + + mask[sub_img] = MAX_PIXEL_VAL + + blur = cv2.blur(mask, (kernel_size, kernel_size)) + pix = np.array(blur) + sub_mask = pix > 128 + + mask_1 = np.zeros_like(b_channel) + mask_1[sub_mask] = MAX_PIXEL_VAL + + return mask_1 + + @staticmethod + def remove_small_area_mask(mask_img: np.ndarray, min_area_size: int) -> np.ndarray: + """Removes small anomalies in the mask + Arguments: + mask_img: the mask image to remove anomalies from + min_area_size: the size of anomalies to look for + Return: + A new mask image with the anomalies removed + """ + mask_array = mask_img > 0 + rel_array = morphology.remove_small_objects(mask_array, min_area_size) + + rel_img = np.zeros_like(mask_img) + rel_img[rel_array] = MAX_PIXEL_VAL + + return rel_img + + @staticmethod + def remove_small_holes_mask(mask_image: np.ndarray, max_hole_size: int) -> np.ndarray: + """Removes small holes from the mask image + Arguments: + mask_image: the mask image to remove holes from + max_hole_size: the maximum size of holes to remove + Return: + A new mask image with the holes removed + """ + mask_array = mask_image > 0 + rel_array = morphology.remove_small_holes(mask_array, max_hole_size) + rel_img = np.zeros_like(mask_image) + rel_img[rel_array] = MAX_PIXEL_VAL + + return rel_img + + @staticmethod + def saturated_pixel_classification(gray_img: np.ndarray, base_mask: np.ndarray, saturated_mask: np.ndarray, + dilate_size: int = 0) -> np.ndarray: + """Returns an image with pixes classified for masking + Arguments: + Returns: + A mask image with the pixels classified + """ + # add saturated area into basic mask + saturated_mask = morphology.binary_dilation(saturated_mask, morphology.diamond(dilate_size)) + + rel_img = np.zeros_like(gray_img) + rel_img[saturated_mask] = MAX_PIXEL_VAL + + label_img, num = morphology.label(rel_img, connectivity=2, return_num=True) + + rel_mask = base_mask + + for idx in range(1, num): + match = (label_img == idx) + + if np.sum(match) > 100000: # if the area is too large, do not add it into basic mask + continue + + if not (match & base_mask).any(): + continue + + rel_mask = rel_mask | match + + return rel_mask + + @staticmethod + def over_saturation_process(rgb_image: np.ndarray, init_mask: np.ndarray, threshold: int = SATURATE_THRESHOLD) -> np.ndarray: + """Removes over saturated areas from an image + Arguments: + rgb_image: the image to process + init_mask: + threshold: The saturation threshold value + Return: + A new image with over saturated pixels removed + """ + # connected component analysis for over saturation pixels + gray_img = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY) + + mask_over = gray_img > threshold + + mask_0 = gray_img < threshold + + src_mask_array = init_mask > 0 + + mask_1 = src_mask_array & mask_0 + + mask_1 = morphology.remove_small_objects(mask_1, SMALL_AREA_THRESHOLD) + + mask_over = morphology.remove_small_objects(mask_over, SMALL_AREA_THRESHOLD) + + rel_mask = __internal__.saturated_pixel_classification(gray_img, mask_1, mask_over, 1) + rel_img = np.zeros_like(gray_img) + rel_img[rel_mask] = MAX_PIXEL_VAL + + return rel_img + + @staticmethod + def gen_saturated_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: + """Generates a mask of over saturated pixels + Arguments: + img: the image to generate the mask from + kernel_size: the size of masking kernel + Returns: + The image mask of over saturated pixels + """ + bin_mask = __internal__.gen_plant_mask(img, kernel_size) + bin_mask = __internal__.remove_small_area_mask(bin_mask, + 500) # 500 is a parameter for number of pixels to be removed as small area + bin_mask = __internal__.remove_small_holes_mask(bin_mask, + 300) # 300 is a parameter for number of pixels to be filled as small holes + + bin_mask = __internal__.over_saturation_process(img, bin_mask, SATURATE_THRESHOLD) + + bin_mask = __internal__.remove_small_holes_mask(bin_mask, 4000) + + return bin_mask + + @staticmethod + def gen_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: + """Generated the mask for plants + Arguments: + img: the image used to mask in plants + kernel_size: the size of the image processing kernel + Return: + A new image mask + """ + bin_mask = __internal__.gen_plant_mask(img, kernel_size) + bin_mask = __internal__.remove_small_area_mask(bin_mask, SMALL_AREA_THRESHOLD) + bin_mask = __internal__.remove_small_holes_mask(bin_mask, + 3000) # 3000 is a parameter for number of pixels to be filled as small holes + + return bin_mask + + @staticmethod + def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: + """Applies the mask to the image + Arguments: + img: the source image to mask + bin_mask: the mask to apply to the image + Return: + A new image that had the mask applied + """ + rgb_mask = cv2.bitwise_and(img, img, mask=bin_mask) + + return rgb_mask + + @staticmethod + def check_saturation(img: np.ndarray) -> list: + """Checks the saturation of an image + Arguments: + img: the image to check + Return: + A list containing the over threshold rate and the under threshold rate + """ + # check how many percent of pix close to 255 or 0 + gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + + over_threshold = gray_img > SATURATE_THRESHOLD + under_threshold = gray_img < 20 # 20 is a threshold to classify low pixel value + + over_rate = float(np.sum(over_threshold)) / float(gray_img.size) + low_rate = float(np.sum(under_threshold)) / float(gray_img.size) + + return [over_rate, low_rate] + + @staticmethod + def get_maskfilename(filename: str) -> str: + """Returns the name of the file to use as a mask. Any path information + in the filename parameter is not returned. + Arguments: + filename: the name of the file to convert to a mask name + Return: + The name of the mask file + """ + base, ext = os.path.splitext(os.path.basename(filename)) + + return base + "_mask" + ext + + +def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> tuple: + """Generates an image mask keeping plants + Arguments: + input_path: the path to the input image + kernel_size: the image kernel size for processing + Return: + A list containing the percent of unmasked pixels and the masked image + """ + # abandon low quality images, mask enhanced + # TODO: cv2 has problems with some RGB geotiffs... + # img = cv2.imread(input_path) + img = np.rollaxis(gdal.Open(input_path).ReadAsArray().astype(np.uint8), 0, 3) + img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) + + # calculate image scores + # pylint: disable=unused-variable + over_rate, low_rate = __internal__.check_saturation(img) + + # TODO: disabling this check for now because it's crashing extractor - generate mask regardless + # if low score, return None + # low_rate is percentage of low value pixels(lower than 20) in the grayscale image, if low_rate > 0.1, return + # aveValue is average pixel value of grayscale image, if aveValue lower than 30 or higher than 195, return + # quality_score is a score from Multiscale Autocorrelation (MAC), if quality_score lower than 13, return + + # saveValue = check_brightness(img) + # quality_score = get_image_quality(input_path) + # if low_rate > 0.1 or aveValue < 30 or aveValue > 195 or quality_score < 13: + # return None, None, None + + # saturated image process + # over_rate is percentage of high value pixels(higher than SATURATE_THRESHOLD) in the grayscale image, if + # over_rate > 0.15, try to fix it use gen_saturated_mask() + if over_rate > 0.15: + bin_mask = __internal__.gen_saturated_mask(img, kernel_size) + else: # normal image process + bin_mask = __internal__.gen_mask(img, kernel_size) + + count = np.count_nonzero(bin_mask) + ratio = count / float(bin_mask.size) + + rgb_mask = __internal__.gen_rgb_mask(img, bin_mask) + + return ratio, rgb_mask + + +class SoilMask(algorithm.Algorithm): + """Masks soil from an image""" + + @property + def supported_file_ext(self) -> tuple: + """Returns a tuple of supported file extensions in lowercase (with the preceeding dot: eg '.tif')""" + return '.tiff', '.tif' + + def check_continue(self, transformer: Environment, check_md: dict, transformer_md: list, + full_md: list) -> tuple: + """Checks if conditions are right for continuing processing + Arguments: + transformer: instance of transformer class + check_md: the metadata for this request + transformer_md: the metadata associated with this transformer + full_md: the full set of original metadata + Return: + Returns a tuple containing the return code for continuing or not, and + an error message if there's an error + """ + # pylint: disable=unused-argument + result = {'code': -1002, 'message': "No TIFF files were specified for processing"} + + # Ensure we have a TIFF file + if check_md and 'list_files' in check_md: + files = check_md['list_files']() + try: + for one_file in files: + ext = os.path.splitext(one_file)[1].lower() + if ext in self.supported_file_ext: + result['code'] = 0 + break + except Exception as ex: + result['code'] = -1 + result['error'] = "Exception caught processing file list: %s" % str(ex) + else: + result['code'] = -1 + result['error'] = "Check metadata parameter is not configured to provide a list of files" + + return (result['code'], result['error']) if 'error' in result else (result['code']) + + def perform_process(self, environment: Environment, check_md: dict, transformer_md: dict, + full_md: list) -> dict: + """Performs the processing of the data + Arguments: + environment: instance of environment class + check_md: the metadata for this request + transformer_md: the metadata associated with this transformer + full_md: the full set of original metadata + Return: + Returns a dictionary with the results of processing + """ + # pylint: disable=unused-argument + result = {} + file_md = [] + + # Loop through the files + try: + for one_file in check_md['list_files'](): + # Check file by type + ext = os.path.splitext(one_file)[1].lower() + if ext not in self.supported_file_ext: + continue + if not os.path.exists(one_file): + logging.warning("Unable to access file '%s'", one_file) + continue + + # Get the image's EPSG code + epsg = geoimage.get_epsg(one_file) + if epsg is None: + logging.debug("Skipping image that is not georeferenced: '%s'", one_file) + continue + + # Get the bounds of the image to see if we can process it. + bounds = geoimage.image_get_geobounds(one_file) + + if bounds is None: + logging.warning("Unable to get bounds of georeferenced image: '%s'", + os.path.basename(one_file)) + continue + + # Get the mask name using the original name as reference + rgb_mask_tif = os.path.join(check_md['working_folder'], __internal__.get_maskfilename(one_file)) + + # Create the mask file + logging.debug("Creating mask file '%s'", rgb_mask_tif) + mask_ratio, mask_rgb = gen_cc_enhanced(one_file) + + # Bands must be reordered to avoid swapping R and B + mask_rgb = cv2.cvtColor(mask_rgb, cv2.COLOR_BGR2RGB) + + transformer_info = environment.generate_transformer_md() + + image_md = __internal__.prepare_metadata_for_geotiff(transformer_info) + geoimage.create_geotiff(mask_rgb, bounds, rgb_mask_tif, epsg, None, False, image_md, compress=True) + + transformer_md = { + 'name': transformer_info['name'], + 'version': transformer_info['version'], + 'ratio': mask_ratio + } + + new_file_md = {'path': rgb_mask_tif, + 'key': ConfigurationSoilmask.transformer_sensor, + 'metadata': { + 'data': transformer_md + } + } + file_md.append(new_file_md) + + result['code'] = 0 + result['file'] = file_md + + except Exception as ex: + result['code'] = -1001 + result['error'] = "Exception caught masking files: %s" % str(ex) + + return result + + +if __name__ == "__main__": + CONFIGURATION = ConfigurationSoilmask() + entrypoint.entrypoint(CONFIGURATION, SoilMask()) diff --git a/transformer.py b/transformer.py deleted file mode 100644 index 8729bea..0000000 --- a/transformer.py +++ /dev/null @@ -1,596 +0,0 @@ -"""Testing instance of transformer -""" - -import logging -import os -import tempfile -import numpy as np -import cv2 - -from osgeo import gdal, osr -# from PIL import Image Used by code that's getting deprecated -from skimage import morphology - -import configuration -import transformer_class - -SATURATE_THRESHOLD = 245 -MAX_PIXEL_VAL = 255 -SMALL_AREA_THRESHOLD = 200 - - -class __internal__(): - """Class for functions intended for internal use only for this file - """ - def __init__(self): - """Performs initialization of class instance - """ - - @staticmethod - def prepare_metadata_for_geotiff(extractor_info=None, terra_md=None): - """Create geotiff-embedded metadata from extractor_info and terraref metadata pieces. - - Keyword arguments: - extractor_info -- details about extractor if applicable - system_md -- cleaned TERRA-REF metadata - """ - extra_metadata = {} - - if (terra_md != None): - extra_metadata["datetime"] = str(terra_md["gantry_variable_metadata"]["datetime"]) - extra_metadata["sensor_id"] = str(terra_md["sensor_fixed_metadata"]["sensor_id"]) - extra_metadata["sensor_url"] = str(terra_md["sensor_fixed_metadata"]["url"]) - experiment_names = [] - for e in terra_md["experiment_metadata"]: - experiment_names.append(e["name"]) - terra_md["experiment_name"] = ", ".join(experiment_names) - - if (extractor_info != None): - extra_metadata["extractor_name"] = str(extractor_info.get("name", "")) - extra_metadata["extractor_version"] = str(extractor_info.get("version", "")) - extra_metadata["extractor_author"] = str(extractor_info.get("author", "")) - extra_metadata["extractor_description"] = str(extractor_info.get("description", "")) - if "repository" in extractor_info and "repUrl" in extractor_info["repository"]: - extra_metadata["extractor_repo"] = str(extractor_info["repository"]["repUrl"]) - else: - extra_metadata["extractor_repo"] = "" - - return extra_metadata - - @staticmethod - def create_geotiff(pixels, gps_bounds, out_path, nodata=-99, asfloat=False, extractor_info=None, system_md=None, - extra_metadata=None, compress=False): - """Generate output GeoTIFF file given a numpy pixel array and GPS boundary. - - Keyword arguments: - pixels -- numpy array of pixel values. - if 2-dimensional array, a single-band GeoTIFF will be created. - if 3-dimensional array, a band will be created for each Z dimension. - gps_bounds -- tuple of GeoTIFF coordinates as ( lat (y) min, lat (y) max, - long (x) min, long (x) max) - out_path -- path to GeoTIFF to be created - nodata -- NoDataValue to be assigned to raster bands; set to None to ignore - float -- whether to use GDT_Float32 data type instead of GDT_Byte (e.g. for decimal numbers) - extractor_info -- details about extractor if applicable - system_md -- cleaned TERRA-REF metadata - extra_metadata -- any metadata to be embedded in geotiff; supersedes extractor_info and system_md - """ - dimensions = np.shape(pixels) - if len(dimensions) == 2: - nrows, ncols = dimensions - channels = 1 - else: - nrows, ncols, channels = dimensions - - geotransform = ( - gps_bounds[2], # upper-left x - (gps_bounds[3] - gps_bounds[2]) / float(ncols), # W-E pixel resolution - 0, # rotation (0 = North is up) - gps_bounds[1], # upper-left y - 0, # rotation (0 = North is up) - -((gps_bounds[1] - gps_bounds[0]) / float(nrows)) # N-S pixel resolution - ) - - # Create output GeoTIFF and set coordinates & projection - if asfloat: - dtype = gdal.GDT_Float32 - else: - dtype = gdal.GDT_Byte - - if compress: - output_raster = gdal.GetDriverByName('GTiff') \ - .Create(out_path, ncols, nrows, channels, dtype, ['COMPRESS=LZW']) - else: - output_raster = gdal.GetDriverByName('GTiff') \ - .Create(out_path, ncols, nrows, channels, dtype) - - output_raster.SetGeoTransform(geotransform) - srs = osr.SpatialReference() - srs.ImportFromEPSG(4326) # google mercator - output_raster.SetProjection(srs.ExportToWkt()) - - if not extra_metadata: - extra_metadata = __internal__.prepare_metadata_for_geotiff(extractor_info, system_md) - - output_raster.SetMetadata(extra_metadata) - - if channels == 3: - # typically 3 channels = RGB channels - # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels) - output_raster.GetRasterBand(1).WriteArray(pixels[:, :, 0].astype('uint8')) - output_raster.GetRasterBand(1).SetColorInterpretation(gdal.GCI_RedBand) - output_raster.GetRasterBand(1).FlushCache() - if nodata: - output_raster.GetRasterBand(1).SetNoDataValue(nodata) - - output_raster.GetRasterBand(2).WriteArray(pixels[:, :, 1].astype('uint8')) - output_raster.GetRasterBand(2).SetColorInterpretation(gdal.GCI_GreenBand) - output_raster.GetRasterBand(2).FlushCache() - if nodata: - output_raster.GetRasterBand(2).SetNoDataValue(nodata) - - output_raster.GetRasterBand(3).WriteArray(pixels[:, :, 2].astype('uint8')) - output_raster.GetRasterBand(3).SetColorInterpretation(gdal.GCI_BlueBand) - output_raster.GetRasterBand(3).FlushCache() - if nodata: - output_raster.GetRasterBand(3).SetNoDataValue(nodata) - - elif channels > 1: - # TODO: Something wonky w/ uint8s --> ending up w/ lots of gaps in data (white pixels) - for chan in range(channels): - band = chan + 1 - output_raster.GetRasterBand(band).WriteArray(pixels[:, :, chan].astype('uint8')) - output_raster.GetRasterBand(band).FlushCache() - if nodata: - output_raster.GetRasterBand(band).SetNoDataValue(nodata) - else: - # single channel image, e.g. temperature - output_raster.GetRasterBand(1).WriteArray(pixels) - output_raster.GetRasterBand(1).FlushCache() - if nodata: - output_raster.GetRasterBand(1).SetNoDataValue(nodata) - - output_raster = None - -# @staticmethod -# def get_image_quality(imgfile: str) -> np.ndarray: -# """Computes and returns the image score for the image file -# Arguments: -# imgfile: the name of the file to compute the score for -# Returns: -# The score for the image -# """ -# img = Image.open(imgfile) -# img = np.array(img) -# -# nrmac = __internal__.MAC(img, img, img) -# -# return nrmac - - @staticmethod - def gen_plant_mask(color_img: np.ndarray, kernel_size: int = 3) -> np.ndarray: - """Generates an image with plants masked in. - Arguments: - color_img: RGB image to mask - kernel_size: masking kernel size - Return: - An RGB image with plants masked in - """ - r_channel = color_img[:, :, 2] - g_channel = color_img[:, :, 1] - b_channel = color_img[:, :, 0] - - sub_img = (g_channel.astype('int') - r_channel.astype('int') - 0) > 0 # normal: -2 - - mask = np.zeros_like(b_channel) - - mask[sub_img] = MAX_PIXEL_VAL - - blur = cv2.blur(mask, (kernel_size, kernel_size)) - pix = np.array(blur) - sub_mask = pix > 128 - - mask_1 = np.zeros_like(b_channel) - mask_1[sub_mask] = MAX_PIXEL_VAL - - return mask_1 - - @staticmethod - def remove_small_area_mask(mask_img: np.ndarray, min_area_size: int) -> np.ndarray: - """Removes small anomalies in the mask - Arguments: - mask_img: the mask image to remove anomalies from - min_area_size: the size of anomalies to look for - Return: - A new mask image with the anomalies removed - """ - mask_array = mask_img > 0 - rel_array = morphology.remove_small_objects(mask_array, min_area_size) - - rel_img = np.zeros_like(mask_img) - rel_img[rel_array] = MAX_PIXEL_VAL - - return rel_img - - @staticmethod - def remove_small_holes_mask(mask_image: np.ndarray, max_hole_size: int) -> np.ndarray: - """Removes small holes from the mask image - Arguments: - mask_image: the mask image to remove holes from - max_hole_size: the maximum size of holes to remove - Return: - A new mask image with the holes removed - """ - mask_array = mask_image > 0 - rel_array = morphology.remove_small_holes(mask_array, max_hole_size) - rel_img = np.zeros_like(mask_image) - rel_img[rel_array] = MAX_PIXEL_VAL - - return rel_img - - @staticmethod - def saturated_pixel_classification(gray_img: np.ndarray, base_mask: np.ndarray, saturated_mask: np.ndarray, - dilate_size: int = 0) -> np.ndarray: - """Returns an image with pixes classified for masking - Arguments: - Returns: - A mask image with the pixels classified - """ - # add saturated area into basic mask - saturated_mask = morphology.binary_dilation(saturated_mask, morphology.diamond(dilate_size)) - - rel_img = np.zeros_like(gray_img) - rel_img[saturated_mask] = MAX_PIXEL_VAL - - label_img, num = morphology.label(rel_img, connectivity=2, return_num=True) - - rel_mask = base_mask - - for idx in range(1, num): - match = (label_img == idx) - - if np.sum(match) > 100000: # if the area is too large, do not add it into basic mask - continue - - if not (match & base_mask).any(): - continue - - rel_mask = rel_mask | match - - return rel_mask - - @staticmethod - def over_saturation_process(rgb_image: np.ndarray, init_mask: np.ndarray, threshold: int = SATURATE_THRESHOLD) -> np.ndarray: - """Removes over saturated areas from an image - Arguments: - rgb_image: the image to process - init_mask: - threshold: The saturation threshold value - Return: - A new image with over saturated pixels removed - """ - # connected component analysis for over saturation pixels - gray_img = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY) - - mask_over = gray_img > threshold - - mask_0 = gray_img < threshold - - src_mask_array = init_mask > 0 - - mask_1 = src_mask_array & mask_0 - - mask_1 = morphology.remove_small_objects(mask_1, SMALL_AREA_THRESHOLD) - - mask_over = morphology.remove_small_objects(mask_over, SMALL_AREA_THRESHOLD) - - rel_mask = __internal__.saturated_pixel_classification(gray_img, mask_1, mask_over, 1) - rel_img = np.zeros_like(gray_img) - rel_img[rel_mask] = MAX_PIXEL_VAL - - return rel_img - - @staticmethod - def gen_saturated_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: - """Generates a mask of over saturated pixels - Arguments: - img: the image to generate the mask from - kernel_size: the size of masking kernel - Returns: - The image mask of over saturated pixels - """ - bin_mask = __internal__.gen_plant_mask(img, kernel_size) - bin_mask = __internal__.remove_small_area_mask(bin_mask, - 500) # 500 is a parameter for number of pixels to be removed as small area - bin_mask = __internal__.remove_small_holes_mask(bin_mask, - 300) # 300 is a parameter for number of pixels to be filled as small holes - - bin_mask = __internal__.over_saturation_process(img, bin_mask, SATURATE_THRESHOLD) - - bin_mask = __internal__.remove_small_holes_mask(bin_mask, 4000) - - return bin_mask - - @staticmethod - def gen_mask(img: np.ndarray, kernel_size: int) -> np.ndarray: - """Generated the mask for plants - Arguments: - img: the image used to mask in plants - kernel_size: the size of the image processing kernel - Return: - A new image mask - """ - bin_mask = __internal__.gen_plant_mask(img, kernel_size) - bin_mask = __internal__.remove_small_area_mask(bin_mask, SMALL_AREA_THRESHOLD) - bin_mask = __internal__.remove_small_holes_mask(bin_mask, - 3000) # 3000 is a parameter for number of pixels to be filled as small holes - - return bin_mask - - @staticmethod - def gen_rgb_mask(img: np.ndarray, bin_mask: np.ndarray) -> np.ndarray: - """Applies the mask to the image - Arguments: - img: the source image to mask - bin_mask: the mask to apply to the image - Return: - A new image that had the mask applied - """ - rgb_mask = cv2.bitwise_and(img, img, mask=bin_mask) - - return rgb_mask - -# @staticmethod -# def rgb2gray(rgb: np.ndarray) -> np.ndarray: -# """Converts RGB image to grey scale -# Arguments: -# rgb: the image to convert -# Return: -# The greyscale image -# """ -# r_channel, g_channel, b_channel = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2] -# gray = 0.2989 * r_channel + 0.5870 * g_channel + 0.1140 * b_channel -# return gray - -# @staticmethod -# def MAC(im1: np.ndarray, im2: np.ndarray, im: np.ndarray) -> np.ndarray: # pylint: disable=invalid-name -# """Calculates an image score of Multiscale Autocorrelation (MAC) -# Arguments: -# Return: -# Returns the scored image -# """ -# h_dim, _, c_dim = im1.shape -# if c_dim > 1: -# im = np.matrix.round(__internal__.rgb2gray(im)) -# im1 = np.matrix.round(__internal__.rgb2gray(im1)) -# im2 = np.matrix.round(__internal__.rgb2gray(im2)) -# # multiscale parameters -# scales = np.array([2, 3, 5]) -# fm_arr = np.zeros(len(scales)) -# for idx, _ in enumerate(scales): -# im1[0: h_dim - 1, :] = im[1:h_dim, :] -# im2[0: h_dim - scales[idx], :] = im[scales[idx]:h_dim, :] -# dif = im * (im1 - im2) -# fm_arr[idx] = np.mean(dif) -# nrmac = np.mean(fm_arr) -# return nrmac - - @staticmethod - def check_saturation(img: np.ndarray) -> list: - """Checks the saturation of an image - Arguments: - img: the image to check - Return: - A list containing the over threshold rate and the under threshold rate - """ - # check how many percent of pix close to 255 or 0 - gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - - over_threshold = gray_img > SATURATE_THRESHOLD - under_threshold = gray_img < 20 # 20 is a threshold to classify low pixel value - - over_rate = float(np.sum(over_threshold)) / float(gray_img.size) - low_rate = float(np.sum(under_threshold)) / float(gray_img.size) - - return over_rate, low_rate - -# @staticmethod -# def check_brightness(img: np.ndarray) -> float: -# """Generates average pixel value from grayscale image -# Arguments: -# img: the source image -# Returns: -# The average pixel value of the image -# """ -# gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) -# -# avg_value = np.average(gray_img) -# -# return avg_value - - @staticmethod - def get_maskfilename(filename: str) -> str: - """Returns the name of the file to use as a mask. Any path information - in the filename parameter is not returned. - Arguments: - filename: the name of the file to convert to a mask name - Return: - The name of the mask file - """ - base, ext = os.path.splitext(os.path.basename(filename)) - - return base + "_mask" + ext - - -def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> tuple: - """Generates an image mask keeping plants - Arguments: - input_path: the path to the input image - kernel_size: the image kernel size for processing - Return: - A list contianing the percent of unmasked pixels and the masked image - """ - # abandon low quality images, mask enhanced - # TODO: cv2 has problems with some RGB geotiffs... - # img = cv2.imread(input_path) - img = np.rollaxis(gdal.Open(input_path).ReadAsArray().astype(np.uint8), 0, 3) - img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) - - # calculate image scores - # pylint: disable=unused-variable - over_rate, low_rate = __internal__.check_saturation(img) - - # TODO: disabling this check for now because it's crashing extractor - generate mask regardless - # if low score, return None - # low_rate is percentage of low value pixels(lower than 20) in the grayscale image, if low_rate > 0.1, return - # aveValue is average pixel value of grayscale image, if aveValue lower than 30 or higher than 195, return - # quality_score is a score from Multiscale Autocorrelation (MAC), if quality_score lower than 13, return - - # saveValue = check_brightness(img) - # quality_score = get_image_quality(input_path) - # if low_rate > 0.1 or aveValue < 30 or aveValue > 195 or quality_score < 13: - # return None, None, None - - # saturated image process - # over_rate is percentage of high value pixels(higher than SATURATE_THRESHOLD) in the grayscale image, if - # over_rate > 0.15, try to fix it use gen_saturated_mask() - if over_rate > 0.15: - bin_mask = __internal__.gen_saturated_mask(img, kernel_size) - else: # normal image process - bin_mask = __internal__.gen_mask(img, kernel_size) - - count = np.count_nonzero(bin_mask) - ratio = count / float(bin_mask.size) - - rgb_mask = __internal__.gen_rgb_mask(img, bin_mask) - - return ratio, rgb_mask - - -def check_continue(transformer: transformer_class.Transformer, check_md: dict, transformer_md: list, - full_md: list) -> tuple: - """Checks if conditions are right for continuing processing - Arguments: - transformer: instance of transformer class - check_md: the metadata for this request - transformer_md: the metadata associated with this transformer - full_md: the full set of original metadata - Return: - Returns a tuple containing the return code for continuing or not, and - an error message if there's an error - """ - # pylint: disable=unused-argument - result = {'code': -1002, 'message': "No TIFF files were specified for processing"} - - # Ensure we have a TIFF file - if check_md and 'list_files' in check_md: - files = check_md['list_files']() - try: - for one_file in files: - ext = os.path.splitext(one_file)[1].lower() - if ext in ('.tiff', '.tif'): - result['code'] = 0 - break - except Exception as ex: - result['code'] = -1 - result['error'] = "Exception caught processing file list: %s" % str(ex) - else: - result['code'] = -1 - result['error'] = "Check metadata parameter is not configured to provide a list of files" - - return (result['code'], result['error']) if 'error' in result else (result['code']) - - -def perform_process(transformer: transformer_class.Transformer, check_md: dict, transformer_md: list, - full_md: list) -> dict: - """Performs the processing of the data - Arguments: - transformer: instance of transformer class' - check_md: the metadata for this request - transformer_md: the metadata associated with this transformer - full_md: the full set of original metadata - Return: - Returns a dictionary with the results of processing - """ - # pylint: disable=unused-argument - result = {} - file_md = [] - - # Loop through the files - try: - for one_file in check_md['list_files'](): - # Check file by type - ext = os.path.splitext(one_file)[1].lower() - if ext not in ('.tiff', '.tif'): - continue - if not os.path.exists(one_file): - logging.warning("Unable to access file '%s'", one_file) - continue - mask_source = one_file - - # Get the image's EPSG code - epsg = transformer.get_image_file_epsg(mask_source) - if epsg is None: - logging.debug("Skipping image that is not georeferenced: '%s'", mask_source) - continue - - # Check that it's geo referenced and transform it if it'sin the wrong coordinate system - if epsg != transformer.default_epsg: - logging.info("Reprojecting image from EPSG %s to default EPSG %s", str(epsg), - str(transformer.default_epsg)) - _, tmp_name = tempfile.mkstemp(dir=check_md['working_folder']) - src = gdal.Open(mask_source) - gdal.Warp(tmp_name, src, dstSRS='EPSG:'+str(transformer.default_epsg)) - mask_source = tmp_name - - # Get the bounds of the image to see if we can process it. - bounds = transformer.get_image_file_geobounds(mask_source) - - if bounds is None: - logging.warning("Unable to get bounds of georeferenced image: '%s'", - os.path.basename(one_file)) - if mask_source != one_file: - os.remove(mask_source) - continue - - # Get the mask name using the original name as reference - rgb_mask_tif = os.path.join(check_md['working_folder'], __internal__.get_maskfilename(one_file)) - - # Create the mask file - logging.debug("Creating mask file '%s'", rgb_mask_tif) - mask_ratio, mask_rgb = gen_cc_enhanced(mask_source) - - # Bands must be reordered to avoid swapping R and B - mask_rgb = cv2.cvtColor(mask_rgb, cv2.COLOR_BGR2RGB) - - transformer_info = transformer.generate_transformer_md() - - __internal__.create_geotiff(mask_rgb, bounds, rgb_mask_tif, None, False, - transformer_info, check_md['context_md'], compress=True) - - # Remove any temporary file - if mask_source != one_file: - os.remove(mask_source) - - transformer_md = { - 'name': transformer_info['name'], - 'version': transformer_info['version'], - 'ratio': mask_ratio - } - - new_file_md = {'path': rgb_mask_tif, - 'key': configuration.TRANSFORMER_SENSOR, - 'metadata': { - 'data': transformer_md - } - } - file_md.append(new_file_md) - - result['code'] = 0 - result['file'] = file_md - - except Exception as ex: - result['code'] = -1001 - result['error'] = "Exception caught masking files: %s" % str(ex) - - return result diff --git a/transformer_class.py b/transformer_class.py deleted file mode 100644 index ece753c..0000000 --- a/transformer_class.py +++ /dev/null @@ -1,311 +0,0 @@ -"""Class instance for Transformer -""" - -import argparse -import datetime -import logging -from osgeo import gdal, osr -from numpy import nan -import piexif -from typing import Optional - -import configuration - -# EXIF tags to look for -EXIF_ORIGIN_TIMESTAMP = 36867 # Capture timestamp -EXIF_TIMESTAMP_OFFSET = 36881 # Timestamp UTC offset (general) -EXIF_ORIGIN_TIMESTAMP_OFFSET = 36881 # Capture timestamp UTC offset - - -class __internal__(): - """Class containing functions for this file only - """ - def __init__(self): - """Perform class level initialization - """ - - @staticmethod - def image_get_geobounds(filename: str) -> list: - """Uses gdal functionality to retrieve recilinear boundaries from the file - - Args: - filename(str): path of the file to get the boundaries from - - Returns: - The upper-left and calculated lower-right boundaries of the image in a list upon success. - The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan - in each position is returned if the boundaries can't be determined - """ - try: - src = gdal.Open(filename) - ulx, xres, _, uly, _, yres = src.GetGeoTransform() - lrx = ulx + (src.RasterXSize * xres) - lry = uly + (src.RasterYSize * yres) - - min_y = min(uly, lry) - max_y = max(uly, lry) - min_x = min(ulx, lrx) - max_x = max(ulx, lrx) - - return [min_y, max_y, min_x, max_x] - except Exception as ex: - logging.info("[image_get_geobounds] Exception caught: %s", str(ex)) - if logging.getLogger().level == logging.DEBUG: - logging.exception("[image_get_geobounds] Exception") - - return [nan, nan, nan, nan] - - @staticmethod - def get_epsg(filename: str) -> Optional[str]: - """Returns the EPSG of the georeferenced image file - Args: - filename(str): path of the file to retrieve the EPSG code from - Return: - Returns the found EPSG code, or None if it's not found or an error ocurred - """ - logger = logging.getLogger(__name__) - - try: - src = gdal.Open(filename) - - proj = osr.SpatialReference(wkt=src.GetProjection()) - - return proj.GetAttrValue('AUTHORITY', 1) - except Exception as ex: - logger.warning("[get_epsg] Exception caught: %s", str(ex)) - if logging.getLogger().level == logging.DEBUG: - logging.exception("[get_epsg] Exception") - - return None - - @staticmethod - def exif_tags_to_timestamp(exif_tags): - """Looks up the origin timestamp and a timestamp offset in the exit tags and returns - a datetime object - Args: - exif_tags(dict): The exif tags to search for timestamp information - Return: - Returns the origin timestamp when found. The return timestamp is adjusted for UTF if - an offset is found. None is returned if a valid timestamp isn't found. - """ - cur_stamp, cur_offset = (None, None) - - def convert_and_clean_tag(value): - """Internal helper function for handling EXIF tag values. Tests for an empty string after - stripping colons, '+', '-', and whitespace [the spec is unclear if a +/- is needed when - the timestamp offset is unknown (and spaces are used)]. - Args: - value(bytes or str): The tag value - Return: - Returns the cleaned up, and converted from bytes, string. Or None if the value is empty - after stripping above characters and whitespace. - """ - if not value: - return None - - # Convert bytes to string - if isinstance(value, bytes): - value = value.decode('UTF-8').strip() - else: - value = value.strip() - - # Check for an empty string after stripping colons - if value: - if not value.replace(":", "").replace("+:", "").replace("-", "").strip(): - value = None - - return None if not value else value - - # Process the EXIF data - if EXIF_ORIGIN_TIMESTAMP in exif_tags: - cur_stamp = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP]) - if not cur_stamp: - return None - - if EXIF_ORIGIN_TIMESTAMP_OFFSET in exif_tags: - cur_offset = convert_and_clean_tag(exif_tags[EXIF_ORIGIN_TIMESTAMP_OFFSET]) - if not cur_offset and EXIF_TIMESTAMP_OFFSET in exif_tags: - cur_offset = convert_and_clean_tag(exif_tags[EXIF_TIMESTAMP_OFFSET]) - - # Format the string to a timestamp and return the result - try: - if not cur_offset: - cur_ts = datetime.datetime.fromisoformat(cur_stamp) - else: - cur_offset = cur_offset.replace(":", "") - cur_ts = datetime.datetime.fromisoformat(cur_stamp + cur_offset) - except Exception as ex: - cur_ts = None - logging.debug("Exception caught converting EXIF tag to timestamp: %s", str(ex)) - - return cur_ts - - @staticmethod - def get_first_timestamp(file_path: str, timestamp: str = None) -> str: - """Looks for a timestamp in the specified file and returns - the earliest timestamp (when compared to the timestamp parameter) - Arguments: - file_path: the path to the file to check - timestamp: the timestamp to compare against (when specified) - Return: - The earliest found timestamp - """ - first_stamp = datetime.datetime.fromisoformat(timestamp) if timestamp else None - try: - tags_dict = piexif.load(file_path) - if tags_dict and "Exif" in tags_dict: - cur_stamp = __internal__.exif_tags_to_timestamp(tags_dict["Exif"]) - if cur_stamp: - first_stamp = cur_stamp if first_stamp is None or cur_stamp < first_stamp else first_stamp - except Exception as ex: - logging.debug("Exception caught getting timestamp from file: %s", file_path) - logging.debug(" %s", str(ex)) - - if first_stamp: - return first_stamp.isoformat() - - return timestamp - - -class Transformer(): - """Generic class for supporting transformers - """ - - def __init__(self, **kwargs): - """Performs initialization of class instance - Arguments: - kwargs: additional parameters passed in to Transformer - """ - # pylint: disable=unused-argument - self.sensor = None - self.args = None - - @property - def default_epsg(self) -> int: - """Returns the current working EPSG code - """ - return 4326 - - @property - def supported_image_file_exts(self): - """Returns the list of supported image file extension strings (in lower case) - """ - return ['tif', 'tiff', 'jpg'] - - def get_image_file_epsg(self, source_path: str) -> str: - """Returns the EPSG of the georeferenced image file - Arguments: - source_path: the path to the image to load the EPSG code from - Return: - Returns the EPSG code loaded from the file. None is returned if there is a problem or the file - doesn't have an EPSG code - """ - # pylint: disable=no-self-use - return __internal__.get_epsg(source_path) - - def get_image_file_geobounds(self, source_path: str) -> list: - """Uses gdal functionality to retrieve rectilinear boundaries from the file - Args: - source_path(str): path of the file to get the boundaries from - Returns: - The upper-left and calculated lower-right boundaries of the image in a list upon success. - The values are returned in following order: min_y, max_y, min_x, max_x. A list of numpy.nan - is returned if the boundaries can't be determined - """ - # pylint: disable=no-self-use - return __internal__.image_get_geobounds(source_path) - - def generate_transformer_md(self) -> dict: - """Generates metadata about this transformer - Returns: - Returns the transformer metadata - """ - # pylint: disable=no-self-use - return { - 'version': configuration.TRANSFORMER_VERSION, - 'name': configuration.TRANSFORMER_NAME, - 'author': configuration.AUTHOR_NAME, - 'description': configuration.TRANSFORMER_DESCRIPTION, - 'repository': {'repUrl': configuration.REPOSITORY} - } - - def add_parameters(self, parser: argparse.ArgumentParser) -> None: - """Adds processing parameters to existing parameters - Arguments: - parser: instance of argparse - """ - # pylint: disable=no-self-use - parser.epilog = configuration.TRANSFORMER_NAME + ' version ' + configuration.TRANSFORMER_VERSION + \ - ' author ' + configuration.AUTHOR_NAME + ' ' + configuration.AUTHOR_EMAIL - - def get_transformer_params(self, args: argparse.Namespace, metadata: list) -> dict: - """Returns a parameter list for processing data - Arguments: - args: result of calling argparse.parse_args - metadata: the loaded metadata - """ - # Disabling this warning to keep code readable - # pylint: disable=too-many-branches - self.args = args - - timestamp, season_name, experiment_name = None, None, None - parsed_metadata = [] - transformer_md = [] - - # Loop through the metadata - for one_metadata in metadata: - # Determine if we're using JSONLD - if 'content' in one_metadata: - parse_md = one_metadata['content'] - else: - parse_md = one_metadata - # Check for legacy 'pipeline' key - if 'pipeline' in parse_md: - parse_md = parse_md['pipeline'] - parsed_metadata.append(parse_md) - - # Get the season, experiment, etc information - if 'observationTimeStamp' in parse_md: - timestamp = parse_md['observationTimeStamp'] - if 'season' in parse_md: - season_name = parse_md['season'] - if 'studyName' in parse_md: - experiment_name = parse_md['studyName'] - - # Check for transformer specific metadata - if configuration.TRANSFORMER_NAME in parse_md: - if isinstance(parse_md[configuration.TRANSFORMER_NAME], list): - transformer_md.extend(parse_md[configuration.TRANSFORMER_NAME]) - else: - transformer_md.append(parse_md[configuration.TRANSFORMER_NAME]) - # Get the list of files, if there are some and find the earliest timestamp if a timestamp - # hasn't been specified yet - file_list = [] - working_timestamp = timestamp - if args.file_list: - for one_file in args.file_list: - # Filter out arguments that are obviously not files - if not one_file.startswith('-'): - file_list.append(one_file) - # Only bother to get a timestamp if we don't have one specified - if timestamp is None: - working_timestamp = __internal__.get_first_timestamp(one_file, working_timestamp) - if timestamp is None and working_timestamp is not None: - timestamp = working_timestamp - - # Prepare our parameters - check_md = {'timestamp': timestamp, - 'season': season_name, - 'experiment': experiment_name, - 'container_name': None, - 'target_container_name': None, - 'trigger_name': None, - 'context_md': None, - 'working_folder': args.working_space, - 'list_files': lambda: file_list - } - - return {'check_md': check_md, - 'transformer_md': transformer_md, - 'full_md': parsed_metadata - } From 9b3949894b5e1c5c261ba2cc2a895911c1c177a7 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Fri, 26 Jun 2020 13:00:43 -0700 Subject: [PATCH 36/42] Pylint changes --- configuration.py | 6 ++++-- generate_docker.py | 21 ++++++++++----------- 2 files changed, 14 insertions(+), 13 deletions(-) diff --git a/configuration.py b/configuration.py index 7ed476c..d375b59 100644 --- a/configuration.py +++ b/configuration.py @@ -2,7 +2,9 @@ """ from agpypeline.configuration import Configuration + class ConfigurationSoilmask(Configuration): + """Configuration information for Soil Mask transformer""" # Silence this error until we have public methods # pylint: disable=too-few-public-methods @@ -21,11 +23,11 @@ class ConfigurationSoilmask(Configuration): # The email of the author of the extractor author_email = 'schnaufer@email.arizona.edu' - # Reposity URI of where the source code lives + # Repository URI of where the source code lives repository = 'https://github.com/Chris-Schnaufer/rgbmask.git' # Contributors to this transformer - contrubutors = ['Max Burnette', 'Zongyang Li', 'Todd Nicholson'] + contributors = ['Max Burnette', 'Zongyang Li', 'Todd Nicholson'] # The sensor associated with the transformer transformer_sensor = 'stereoTop' diff --git a/generate_docker.py b/generate_docker.py index bf0cb4c..b836d6d 100755 --- a/generate_docker.py +++ b/generate_docker.py @@ -4,7 +4,7 @@ """ import argparse -import configuration +from configuration import ConfigurationSoilmask # The template file name for Dockerfile DOCKERFILE_TEMPLATE_FILE_NAMES = ["Dockerfile.template"] @@ -12,6 +12,7 @@ # The default docker image to use DEFAULT_DOCKER_IMAGE = 'agpipeline/gantry-base-image:latest' + def determine_base_image() -> str: """Determines the base image to use in the dockerfile Return: @@ -26,27 +27,24 @@ def determine_base_image() -> str: return args.base_image + def generate_dockerfile(base_image_name: str) -> None: - """Genertes a Dockerfile file using the configured information + """Generates a Dockerfile file using the configured information """ # pylint: disable=global-statement global DOCKERFILE_TEMPLATE_FILE_NAMES missing = [] - if not hasattr(configuration, 'TRANSFORMER_NAME') or not configuration.TRANSFORMER_NAME: + if not hasattr(ConfigurationSoilmask, 'transformer_name') or not ConfigurationSoilmask.transformer_name: missing.append("Transformer name") - if not hasattr(configuration, 'AUTHOR_NAME') or not configuration.AUTHOR_NAME: + if not hasattr(ConfigurationSoilmask, 'author_name') or not ConfigurationSoilmask.author_name: missing.append("Author name") - if not hasattr(configuration, 'AUTHOR_EMAIL') or not configuration.AUTHOR_EMAIL: + if not hasattr(ConfigurationSoilmask, 'author_email') or not ConfigurationSoilmask.author_email: missing.append("Author email") if missing: raise RuntimeError("One or more configuration fields aren't defined in configuration.py: " \ + ", ".join(missing)) - new_name = configuration.TRANSFORMER_NAME.strip().replace(' ', '_').replace('\t', '_').\ - replace('\n', '_').replace('\r', '_') - extractor_name = new_name.lower() - for template_name in DOCKERFILE_TEMPLATE_FILE_NAMES: template = [line.rstrip('\n') for line in open(template_name, "r")] template_len = len('.template') @@ -54,13 +52,14 @@ def generate_dockerfile(base_image_name: str) -> None: with open(dockerfile_name, 'w') as out_file: for line in template: if line.startswith('LABEL maintainer='): - out_file.write("LABEL maintainer=\"{0} <{1}>\"\n".format(configuration.AUTHOR_NAME, \ - configuration.AUTHOR_EMAIL)) + out_file.write("LABEL maintainer=\"{0} <{1}>\"\n".format(ConfigurationSoilmask.author_name, \ + ConfigurationSoilmask.author_email)) elif line.startswith('FROM base-image'): out_file.write("FROM {0}\n".format(base_image_name)) else: out_file.write("{0}\n".format(line)) + # Make the call to generate the file if __name__ == "__main__": print('Configuring Dockerfile') From 5db80884150e04b06fb4c6bc7e5cc0ccc128ba05 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Fri, 26 Jun 2020 16:17:31 -0700 Subject: [PATCH 37/42] Missed a name change --- soilmask.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/soilmask.py b/soilmask.py index c6633d6..550f8d3 100644 --- a/soilmask.py +++ b/soilmask.py @@ -308,11 +308,11 @@ def supported_file_ext(self) -> tuple: """Returns a tuple of supported file extensions in lowercase (with the preceeding dot: eg '.tif')""" return '.tiff', '.tif' - def check_continue(self, transformer: Environment, check_md: dict, transformer_md: list, + def check_continue(self, environment: Environment, check_md: dict, transformer_md: list, full_md: list) -> tuple: """Checks if conditions are right for continuing processing Arguments: - transformer: instance of transformer class + environment: instance of environment class check_md: the metadata for this request transformer_md: the metadata associated with this transformer full_md: the full set of original metadata From 3beebe9794505d69b184354e656aa9a3156891b8 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Mon, 29 Jun 2020 16:07:22 -0700 Subject: [PATCH 38/42] Updated Dockerfile agypeline library support --- Dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Dockerfile b/Dockerfile index 2ee935b..0dee2bf 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,4 +1,4 @@ -FROM agpypeline +FROM agdrone/agpypeline:1.0 LABEL maintainer="Chris Schnaufer " # Start installing things From 1159c880f37870148c694fa26cd7becc79cd0b43 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Tue, 30 Jun 2020 13:06:10 -0700 Subject: [PATCH 39/42] Adding agpypeline library and some minor channges --- Dockerfile | 3 ++- requirements.txt | 2 ++ soilmask.py | 5 +---- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/Dockerfile b/Dockerfile index 0dee2bf..7ec2dcb 100644 --- a/Dockerfile +++ b/Dockerfile @@ -33,4 +33,5 @@ USER root RUN chmod a+x /home/extractor/soilmask.py USER extractor -ENTRYPOINT ["/home/extractor/soilmask.py"] \ No newline at end of file +ENTRYPOINT ["/home/extractor/soilmask.py"] + diff --git a/requirements.txt b/requirements.txt index abd49b6..e90633d 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,4 @@ scikit-image opencv-python +agpypeline + diff --git a/soilmask.py b/soilmask.py index 550f8d3..c20b48a 100644 --- a/soilmask.py +++ b/soilmask.py @@ -264,8 +264,6 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> tuple: A list containing the percent of unmasked pixels and the masked image """ # abandon low quality images, mask enhanced - # TODO: cv2 has problems with some RGB geotiffs... - # img = cv2.imread(input_path) img = np.rollaxis(gdal.Open(input_path).ReadAsArray().astype(np.uint8), 0, 3) img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) @@ -273,13 +271,12 @@ def gen_cc_enhanced(input_path: str, kernel_size: int = 3) -> tuple: # pylint: disable=unused-variable over_rate, low_rate = __internal__.check_saturation(img) - # TODO: disabling this check for now because it's crashing extractor - generate mask regardless # if low score, return None # low_rate is percentage of low value pixels(lower than 20) in the grayscale image, if low_rate > 0.1, return # aveValue is average pixel value of grayscale image, if aveValue lower than 30 or higher than 195, return # quality_score is a score from Multiscale Autocorrelation (MAC), if quality_score lower than 13, return - # saveValue = check_brightness(img) + # aveValue = check_brightness(img) # quality_score = get_image_quality(input_path) # if low_rate > 0.1 or aveValue < 30 or aveValue > 195 or quality_score < 13: # return None, None, None From 9d1e74b9d6f4272067bb331ecc63d4a4c62e0066 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Tue, 30 Jun 2020 13:13:08 -0700 Subject: [PATCH 40/42] Removing unneeded file --- .github/workflows/transformer_class.py | 49 -------------------------- 1 file changed, 49 deletions(-) delete mode 100644 .github/workflows/transformer_class.py diff --git a/.github/workflows/transformer_class.py b/.github/workflows/transformer_class.py deleted file mode 100644 index 56417e2..0000000 --- a/.github/workflows/transformer_class.py +++ /dev/null @@ -1,49 +0,0 @@ -"""Class instance for Transformer -""" - -import argparse - -# pylint: disable=unused-argument -class Transformer(): - """Generic class for supporting transformers - """ - def __init__(self, **kwargs): - """Performs initialization of class instance - Arguments: - kwargs: additional parameters passed into Transformer instance - """ - self.args = None - - def add_parameters(self, parser: argparse.ArgumentParser) -> None: - """Adds processing parameters to existing parameters - Arguments: - parser: instance of argparse - """ - - # pylint: disable=no-self-use - def get_transformer_params(self, args: argparse.Namespace, metadata: list) -> dict: - """Returns a parameter list for processing data - Arguments: - args: result of calling argparse.parse_args - metadata: the list of loaded metadata - Return: - A dictionary of parameter names and value to pass to transformer - """ - self.args = args - - params = {} - return params - - # pylint: disable=no-self-use - def retrieve_files(self, transformer_params: dict, metadata: list) -> tuple: - """Retrieves files as needed to make them available for processing - Arguments: - transformer_params: the values returned from get_transformer_params() call - metadata: the loaded metadata - Return: - A tuple consisting of the return code and an optional error message. - Notes: - A negative return code is considered an error and an associated message, if specified, - will be treated as such. - """ - return 0, "everything's in order" From bfa4569aaa3154b649c5a1db6cdb2b99d9e00fa8 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Thu, 9 Jul 2020 10:36:58 -0700 Subject: [PATCH 41/42] Adding packages.txt per PR comments --- packages.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 packages.txt diff --git a/packages.txt b/packages.txt new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/packages.txt @@ -0,0 +1 @@ + From 3f24ff18c31830267c7541f29065220dafbe0d32 Mon Sep 17 00:00:00 2001 From: Chris Schnaufer Date: Tue, 14 Jul 2020 13:50:32 -0700 Subject: [PATCH 42/42] Cleaning up repo --- .gitignore | 113 +++++++++++++++++++++++++++++++++++++++++++-- environment.yml | 93 ------------------------------------- generate_docker.py | 68 --------------------------- 3 files changed, 110 insertions(+), 164 deletions(-) delete mode 100644 environment.yml delete mode 100755 generate_docker.py diff --git a/.gitignore b/.gitignore index 2030de3..60ab957 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,111 @@ -.idea/* -*.pyc +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# pyenv +.python-version + +# celery beat schedule file +celerybeat-schedule + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ + +# pycharm +.idea + +# Testing folder test -.venv \ No newline at end of file + diff --git a/environment.yml b/environment.yml deleted file mode 100644 index 11c9b79..0000000 --- a/environment.yml +++ /dev/null @@ -1,93 +0,0 @@ -name: null -channels: - - conda-forge - - defaults -dependencies: - - _libgcc_mutex=0.1=conda_forge - - _openmp_mutex=4.5=1_llvm - - bzip2=1.0.8=h516909a_2 - - ca-certificates=2020.4.5.1=hecc5488_0 - - cairo=1.16.0=hcf35c78_1003 - - certifi=2020.4.5.1=py38h32f6830_0 - - dbus=1.13.6=he372182_0 - - expat=2.2.9=he1b5a44_2 - - ffmpeg=4.2=h167e202_0 - - fontconfig=2.13.1=h86ecdb6_1001 - - freetype=2.10.1=he06d7ca_0 - - gettext=0.19.8.1=hc5be6a0_1002 - - giflib=5.2.1=h516909a_2 - - glib=2.64.2=h6f030ca_0 - - gmp=6.2.0=he1b5a44_2 - - gnutls=3.6.5=hd3a4fd2_1002 - - graphite2=1.3.13=he1b5a44_1001 - - gst-plugins-base=1.14.5=h0935bb2_2 - - gstreamer=1.14.5=h36ae1b5_2 - - harfbuzz=2.4.0=h9f30f68_3 - - hdf5=1.10.6=nompi_h3c11f04_100 - - icu=64.2=he1b5a44_1 - - jasper=1.900.1=h07fcdf6_1006 - - jpeg=9c=h14c3975_1001 - - lame=3.100=h14c3975_1001 - - ld_impl_linux-64=2.34=h53a641e_0 - - libblas=3.8.0=16_openblas - - libcblas=3.8.0=16_openblas - - libclang=9.0.1=default_hde54327_0 - - libffi=3.2.1=he1b5a44_1007 - - libgcc-ng=9.2.0=h24d8f2e_2 - - libgfortran-ng=7.3.0=hdf63c60_5 - - libiconv=1.15=h516909a_1006 - - liblapack=3.8.0=16_openblas - - liblapacke=3.8.0=16_openblas - - libllvm9=9.0.1=he513fc3_1 - - libopenblas=0.3.9=h5ec1e0e_0 - - libopencv=4.2.0=py38_6 - - libpng=1.6.37=hed695b0_1 - - libstdcxx-ng=9.2.0=hdf63c60_2 - - libtiff=4.1.0=hc3755c2_3 - - libuuid=2.32.1=h14c3975_1000 - - libwebp=1.0.2=h56121f0_5 - - libxcb=1.13=h14c3975_1002 - - libxkbcommon=0.10.0=he1b5a44_0 - - libxml2=2.9.10=hee79883_0 - - llvm-openmp=10.0.0=hc9558a2_0 - - lz4-c=1.9.2=he1b5a44_1 - - ncurses=6.1=hf484d3e_1002 - - nettle=3.4.1=h1bed415_1002 - - nspr=4.25=he1b5a44_0 - - nss=3.47=he751ad9_0 - - numpy=1.18.4=py38h8854b6b_0 - - opencv=4.2.0=py38_6 - - openh264=1.8.0=hdbcaa40_1000 - - openssl=1.1.1g=h516909a_0 - - pcre=8.44=he1b5a44_0 - - pip=20.1=pyh9f0ad1d_0 - - pixman=0.38.0=h516909a_1003 - - pthread-stubs=0.4=h14c3975_1001 - - py-opencv=4.2.0=py38h23f93f0_6 - - python=3.8.2=he5300dc_7_cpython - - python_abi=3.8=1_cp38 - - qt=5.12.5=hd8c4c69_1 - - readline=8.0=hf8c457e_0 - - setuptools=46.1.3=py38h32f6830_0 - - sqlite=3.30.1=hcee41ef_0 - - tk=8.6.10=hed695b0_0 - - wheel=0.34.2=py_1 - - x264=1!152.20180806=h14c3975_0 - - xorg-kbproto=1.0.7=h14c3975_1002 - - xorg-libice=1.0.10=h516909a_0 - - xorg-libsm=1.2.3=h84519dc_1000 - - xorg-libx11=1.6.9=h516909a_0 - - xorg-libxau=1.0.9=h14c3975_0 - - xorg-libxdmcp=1.1.3=h516909a_0 - - xorg-libxext=1.3.4=h516909a_0 - - xorg-libxrender=0.9.10=h516909a_1002 - - xorg-renderproto=0.11.1=h14c3975_1002 - - xorg-xextproto=7.3.0=h14c3975_1002 - - xorg-xproto=7.0.31=h14c3975_1007 - - xz=5.2.5=h516909a_0 - - zlib=1.2.11=h516909a_1006 - - zstd=1.4.4=h6597ccf_3 - - pip: - - gdal==2.2.2 - - setuptools==46.2.0 -prefix: /scif/apps/soilmask/conda \ No newline at end of file diff --git a/generate_docker.py b/generate_docker.py deleted file mode 100755 index b836d6d..0000000 --- a/generate_docker.py +++ /dev/null @@ -1,68 +0,0 @@ -#!/usr/bin/env python3 - -"""Generated Dockerfile from a template -""" - -import argparse -from configuration import ConfigurationSoilmask - -# The template file name for Dockerfile -DOCKERFILE_TEMPLATE_FILE_NAMES = ["Dockerfile.template"] - -# The default docker image to use -DEFAULT_DOCKER_IMAGE = 'agpipeline/gantry-base-image:latest' - - -def determine_base_image() -> str: - """Determines the base image to use in the dockerfile - Return: - The name of the base image to use - """ - parser = argparse.ArgumentParser() - - parser.add_argument('base_image', nargs='?', default=DEFAULT_DOCKER_IMAGE, - help='the docker image to use as the base for this transformer') - - args = parser.parse_args() - - return args.base_image - - -def generate_dockerfile(base_image_name: str) -> None: - """Generates a Dockerfile file using the configured information - """ - # pylint: disable=global-statement - global DOCKERFILE_TEMPLATE_FILE_NAMES - - missing = [] - if not hasattr(ConfigurationSoilmask, 'transformer_name') or not ConfigurationSoilmask.transformer_name: - missing.append("Transformer name") - if not hasattr(ConfigurationSoilmask, 'author_name') or not ConfigurationSoilmask.author_name: - missing.append("Author name") - if not hasattr(ConfigurationSoilmask, 'author_email') or not ConfigurationSoilmask.author_email: - missing.append("Author email") - if missing: - raise RuntimeError("One or more configuration fields aren't defined in configuration.py: " \ - + ", ".join(missing)) - - for template_name in DOCKERFILE_TEMPLATE_FILE_NAMES: - template = [line.rstrip('\n') for line in open(template_name, "r")] - template_len = len('.template') - dockerfile_name = template_name[:(template_len * -1)] - with open(dockerfile_name, 'w') as out_file: - for line in template: - if line.startswith('LABEL maintainer='): - out_file.write("LABEL maintainer=\"{0} <{1}>\"\n".format(ConfigurationSoilmask.author_name, \ - ConfigurationSoilmask.author_email)) - elif line.startswith('FROM base-image'): - out_file.write("FROM {0}\n".format(base_image_name)) - else: - out_file.write("{0}\n".format(line)) - - -# Make the call to generate the file -if __name__ == "__main__": - print('Configuring Dockerfile') - BASE = determine_base_image() - print('Using base image "%s"' % BASE) - generate_dockerfile(BASE)

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