Learn how to implement YOLOv5 object detection for chess pieces in under 15 minutes using Python and OpenCV. Explore the process of obtaining, managing, and augmenting a chess dataset with Roboflow. Train the model using Google Colab and cloud ML, then test it on a chess dataset split. Discover how to set up YOLOv5 parameters, train the model, and download the weights with minimal setup. Follow along to create an AI capable of detecting chess pieces, potentially leading to applications in move recording and player coaching.
Chess Pieces Object Detection - Queens Gambit - OpenCV Python - Computer Vision - 2021
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Overview
Syllabus
Introduction
Stay till the end
Dataset
Dataset Health Checker
Exporting the Dataset
AutoML Train
After Training
Host Web API - Inference
Yolov5 Training in Colab
Yolov5 Colab Inference
Conclusion
Taught by
Augmented Startups
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