Open kumarutkarsh1248 opened 1 month ago
It's a set of predefined bounding boxes at different (fixed) positions and sizes. Rather than directly predicting bounding box coordinates, this version of YOLO predicts how each of these predefined bounding boxes (anchors) are moved and scaled to fit objects in the image.
Hi @hollance, I'm currently working on an ONNX converter for the MLPack framework (a C++ machine learning framework). I've successfully developed an initial prototype for the ONNX-MLPack converter, which works fine with the yolov2.onnx model you provided since it has a simple graph. Now, I'm trying to test my converter with the yolov3.onnx models I found online, but all of them seem to have very complex graphs.
these are some of the yolov3.onnx models i found online but all have very complex graph https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/yolov3 https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/tiny-yolov3
if you have worked on yolov3.onnx then could you please provide some yolov3.onnx model with simpler graph
In your article explaining how to use the yolo model what is this anchors list![Screenshot from 2024-07-11 12-54-58](https://github.com/hollance/Forge/assets/118059940/58d9458f-308d-487a-ada5-b75a17c90c38)