In this step, we test our detector on cat and dog images and videos located in TrainYourOwnYOLO/Data/Source_Images/Test_Images. If you like to test the detector on your own images or videos, place them in the Test_Images folder.
To detect objects run the detector script from within the TrainYourOwnYOLO/3_Inference directory:.
python Detector.py
The outputs are saved to TrainYourOwnYOLO/Data/Source_Images/Test_Image_Detection_Results. The outputs include the original images with bounding boxes and confidence scores as well as a file called Detection_Results.csv containing the image file paths and the bounding box coordinates. For videos, the output files are videos with bounding boxes and confidence scores. For real-time detection use python Detector.py --webcam this will open up your webcam and detect your data classes. To list available command line options run python Detector.py -h.
Congratulations on building your own custom YOLOv3 computer vision application.
I hope you enjoyed this tutorial and I hope it helped you get our own computer vision project off the ground:
- Please star ⭐ this repo to get notifications on future improvements and
- Please fork 🍴 this repo if you like to use it as part of your own project.