YOLO v3 Objects Detection with Custom Data

Build your own Detector based on YOLO v3

The Course

Training YOLO v3 for Objects Detection with Custom Data. Build your own detector by labelling, training and testing on image, video and in real time with camera. Available here: https://www.udemy.com/course/training-yolo-v3-for-objects-detection-with-custom-data/

Detections on images (example)

Content of the Course

• Section 1: Quick Win. Simple Object Detection by thresholding with colour mask
• Section 2: Apply trained YOLO v3 and OpenCV to the Objects Detection on image, video and in real time with camera
• Section 3: Label own dataset and structure files in YOLO format
• Section 4: Create custom dataset from huge existing one and structure files in YOLO format
• Section 5: Convert existing dataset and structure files in YOLO format
• Section 6: Train YOLO v3 with prepared datasets in Darknet framework
• Section 7: Build own PyQt user's interface (GUI) for Objects Detection based on YOLO v3 algorithm

You will be able to

→ Apply trained YOLO v3
→ Label dataset in YOLO format
→ Create custom dataset in YOLO format
→ Convert existing dataset of Traffic Signs in YOLO format
→ Train YOLO v3
→ Build PyQt GUI

Concept Map of the Course

Join the Course

🎓 👉 https://www.udemy.com/course/training-yolo-v3-for-objects-detection-with-custom-data/

MIT License

Copyright (c) 2020 Valentyn N Sichkar

github.com/sichkar-valentyn