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In my experience, Yolo-V9-S with coco trained weights (and used on subset of classes - 23 of them) exceeds accuracy of original implementation of yolov9 repo (also stock coco weights and 23 classes).
That sounds great. Have you also tried larger models like the c model? Did you make any changes to the repository? Did you use the COCO pretrained weights from the official yolov9 repo? And what was the dataset you finetuned / tested on?
I am surprised that you even exceeded the performance, because this new repository deactivates some strong data augmentations like Mixup?
Hi,
to what extent could you already reproduce the results of the official YOLOv9 (and YOLOv7) repository?
Best wishes
Johannes
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