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XingZeng307 · Apr 28, 2021 · 643a20b · 643a20b
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-# YOLOv5_with_BiFPN
+# YOLOv5_with_BiFPN
+
+YOLOv5 implementation is completely from the original repository (https://github.com/ultralytics/yolov5). 
+This repo is mainly for replacing PANet with BiFPN in YOLOv5, which you can check in models/yolov5x.yaml. I didn't use the exact same BiFPN in the paper, while I try to be consistent with yolov5, so still three scale predictions.
+
+# Training
+
+python train.py --img 640 --batch 8 --epochs 200 --data CUB.yaml --weights '' --cfg yolov5x.yaml
+
+I didn't use pre-trained weights since the architecture changes a bit. And as for the performance, I will check more dataset and update it.
+
+
+# Reference
+
+https://github.com/ultralytics/yolov5
+
+https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch/tree/15403b5371a64defb2a7c74e162c6e880a7f462c
+
+Mingxing Tan, Ruoming Pang, and Quoc V Le. EfficientDet: Scalable and efficient object detection. In Proceedings
+of the IEEE Conference on Computer Vision and Pattern
+Recognition (CVPR), 2020.
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