OpenCV vs YOLO for Small Object Detection

Well, not really one vs the other but how to get the best of both worlds!
Small object detection is a tough nut to crack, especially when it comes to tiny trading signals on a complex stock chart. In this video, I tackle this challenge head-on, using a two-stage approach. First, I leverage OpenCV to create a fast initial detection algorithm. Then, I use these initial detections to train a YOLO model, which, combined with the SAHI method, significantly improves the accuracy and precision of those green and red triangles. This is an example of how to combine "classic" image processing with modern deep learning techniques for real-world applications.
(text generated by Gemini)