How to detect small objects in (very) large images

In this blog post, ML6 presents a solution for detecting small objects in very large images using a combination of image tiling and object detection algorithms. The blog post explains the challenges of conventional object detection models on such images and introduces a method to divide the image into smaller tiles and perform object detection on each tile individually.

The blog post also provides practical examples of implementing this approach using the YOLOv5 object detection model and the OpenCV library. ML6 highlights the benefits of using this method and emphasizes the importance of careful tuning to achieve optimal performance.

Overall, the blog post offers a solution for detecting small objects in very large images that is implemented through a combination of image tiling and object detection algorithms. We provide practical examples and highlights the importance of tuning to achieve optimal performance.

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