How to Make YOLOv5 Interpretable using GradCAM
In this explanation, I’ll be discussing methods for achieving interpretability in YOLOv5, a popular object detection model. While there have been several attempts to make YOLOv5 interpretable, it’s worth noting that none of these methods are currently compatible with the latest version of the model. My work is the marriage between PyTorch-GradCAM and YOLOv5. GitHub - jacobgil/pytorch-grad-cam: Advanced AI Explainability for computer vision GitHub - ultralytics/yolov5: YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite Usage I want to use your work....