Add ios lidar (#762)

This PR add the possibility to work with IOS lidar as well as texture
rgb-d image within rerun

<img width="1800" alt="Screenshot 2025-01-22 at 09 20 50"
src="https://github.com/user-attachments/assets/97ec6efe-db79-437b-9b4b-6f254da38333"
/>

examples/depth_camera/ios-dev.yaml

@@ -0,0 +1,16 @@
+nodes:
+  - id: camera
+    build: pip install -e ../../node-hub/dora-ios-lidar
+    path: dora-ios-lidar
+    inputs:
+      tick: dora/timer/millis/20
+    outputs:
+      - image
+      - depth
+
+  - id: plot
+    build: pip install -e ../../node-hub/dora-rerun
+    path: dora-rerun
+    inputs:
+      image: camera/image
+      depth: camera/depth

examples/depth_camera/ios.yaml

@@ -0,0 +1,16 @@
+nodes:
+  - id: camera
+    build: pip install dora-ios-lidar
+    path: dora-ios-lidar
+    inputs:
+      tick: dora/timer/millis/20
+    outputs:
+      - image
+      - depth
+
+  - id: plot
+    build: pip install dora-rerun
+    path: dora-rerun
+    inputs:
+      image: camera/image
+      depth: camera/depth

examples/realsense/camera_rerun.yaml → examples/depth_camera/realsense-dev.yaml

@@ -1,20 +1,17 @@
 nodes:
   - id: camera
     build: pip install -e ../../node-hub/dora-pyrealsense
-    path: dora-pyrealsense
+    path: sudo
+    args: dora-pyrealsense
     inputs:
       tick: dora/timer/millis/20
     outputs:
       - image
       - depth
-    env:
-      IMAGE_WIDTH: 640
-      IMAGE_HEIGHT: 480
 
   - id: plot
     build: pip install -e ../../node-hub/dora-rerun
     path: dora-rerun
     inputs:
       image: camera/image
       world/camera/depth: camera/depth
-

examples/depth_camera/realsense.yaml

@@ -0,0 +1,16 @@
+nodes:
+  - id: camera
+    build: pip install dora-pyrealsense
+    path: dora-pyrealsense
+    inputs:
+      tick: dora/timer/millis/20
+    outputs:
+      - image
+      - depth
+
+  - id: plot
+    build: pip install dora-rerun
+    path: dora-rerun
+    inputs:
+      image: camera/image
+      depth: camera/depth

node-hub/dora-ios-lidar/README.md

@@ -0,0 +1,40 @@
+# dora-ios-lidar
+
+## Getting started
+
+- Install it with pip:
+
+```bash
+pip install -e .
+```
+
+- Make sure to install `record3d` app on your IOS device.
+- Buy the USB connection package to start streaming on USB.
+
+## Contribution Guide
+
+- Format with [ruff](https://docs.astral.sh/ruff/):
+
+```bash
+ruff check . --fix
+```
+
+- Lint with ruff:
+
+```bash
+ruff check .
+```
+
+- Test with [pytest](https://github.com/pytest-dev/pytest)
+
+```bash
+pytest . # Test
+```
+
+## YAML Specification
+
+## Examples
+
+## License
+
+dora-ios-lidar's code are released under the MIT License

node-hub/dora-ios-lidar/dora_ios_lidar/__init__.py

@@ -0,0 +1,11 @@
+import os
+
+# Define the path to the README file relative to the package directory
+readme_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "README.md")
+
+# Read the content of the README file
+try:
+    with open(readme_path, "r", encoding="utf-8") as f:
+        __doc__ = f.read()
+except FileNotFoundError:
+    __doc__ = "README file not found."

node-hub/dora-ios-lidar/dora_ios_lidar/__main__.py

@@ -0,0 +1,5 @@
+from .main import main
+
+
+if __name__ == "__main__":
+    main()

node-hub/dora-ios-lidar/dora_ios_lidar/main.py

@@ -0,0 +1,109 @@
+from threading import Event
+
+import cv2
+import numpy as np
+import pyarrow as pa
+from dora import Node
+from record3d import Record3DStream
+
+
+class DemoApp:
+    def __init__(self):
+        self.event = Event()
+        self.session = None
+        self.DEVICE_TYPE__TRUEDEPTH = 0
+        self.DEVICE_TYPE__LIDAR = 1
+        self.stop = False
+
+    def on_new_frame(self):
+        """
+        This method is called from non-main thread, therefore cannot be used for presenting UI.
+        """
+        self.event.set()  # Notify the main thread to stop waiting and process new frame.
+
+    def on_stream_stopped(self):
+        self.stop = True
+        print("Stream stopped")
+
+    def connect_to_device(self, dev_idx):
+        print("Searching for devices")
+        devs = Record3DStream.get_connected_devices()
+        print("{} device(s) found".format(len(devs)))
+        for dev in devs:
+            print("\tID: {}\n".format(dev.product_id))
+
+        if len(devs) <= dev_idx:
+            raise RuntimeError(
+                "Cannot connect to device #{}, try different index.".format(dev_idx)
+            )
+
+        dev = devs[dev_idx]
+        self.session = Record3DStream()
+        self.session.on_new_frame = self.on_new_frame
+        self.session.on_stream_stopped = self.on_stream_stopped
+        self.session.connect(dev)  # Initiate connection and start capturing
+
+    def get_intrinsic_mat_from_coeffs(self, coeffs):
+        return np.array(
+            [[coeffs.fx, 0, coeffs.tx], [0, coeffs.fy, coeffs.ty], [0, 0, 1]]
+        )
+
+    def start_processing_stream(self):
+        node = Node()
+
+        for event in node:
+            if self.stop:
+                break
+            if event["type"] == "INPUT":
+                if event["id"] == "TICK":
+                    self.event.wait()  # Wait for new frame to arrive
+
+                    # Copy the newly arrived RGBD frame
+                    depth = self.session.get_depth_frame()
+                    rgb = self.session.get_rgb_frame()
+                    intrinsic_mat = self.get_intrinsic_mat_from_coeffs(
+                        self.session.get_intrinsic_mat()
+                    )
+
+                    if depth.shape != rgb.shape:
+                        rgb = cv2.resize(rgb, (depth.shape[1], depth.shape[0]))
+
+                    node.send_output(
+                        "image",
+                        pa.array(rgb.ravel()),
+                        metadata={
+                            "encoding": "rgb8",
+                            "width": rgb.shape[1],
+                            "height": rgb.shape[0],
+                        },
+                    )
+
+                    node.send_output(
+                        "depth",
+                        pa.array(depth.ravel().astype(np.float64())),
+                        metadata={
+                            "width": depth.shape[1],
+                            "height": depth.shape[0],
+                            "encoding": "CV_64F",
+                            "focal": [
+                                int(intrinsic_mat[0, 0]),
+                                int(intrinsic_mat[1, 1]),
+                            ],
+                            "resolution": [
+                                int(intrinsic_mat[0, 2]),
+                                int(intrinsic_mat[1, 2]),
+                            ],
+                        },
+                    )
+
+            self.event.clear()
+
+
+def main():
+    app = DemoApp()
+    app.connect_to_device(dev_idx=0)
+    app.start_processing_stream()
+
+
+if __name__ == "__main__":
+    main()

node-hub/dora-ios-lidar/pyproject.toml

@@ -0,0 +1,20 @@
+[project]
+name = "dora-ios-lidar"
+version = "0.0.0"
+authors = [{ name = "Your Name", email = "[email protected]" }]
+description = "dora-ios-lidar"
+license = { text = "MIT" }
+readme = "README.md"
+requires-python = ">=3.8"
+
+dependencies = [
+    "dora-rs >= 0.3.6",
+    "opencv-python>=4.11.0.86",
+    "record3d>=1.4",
+]
+
+[dependency-groups]
+dev = ["pytest >=8.1.1", "ruff >=0.9.1"]
+
+[project.scripts]
+dora-ios-lidar = "dora_ios_lidar.main:main"

node-hub/dora-ios-lidar/tests/test_dora_ios_lidar.py

@@ -0,0 +1,9 @@
+import pytest
+
+
+def test_import_main():
+    from dora_ios_lidar.main import main
+
+    # Check that everything is working, and catch dora Runtime Exception as we're not running in a dora dataflow.
+    with pytest.raises(RuntimeError):
+        main()