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@@ -125,7 +125,7 @@ python train.py --cuda -d coco --root path/to/COCO -v yolov1 -bs 16 --max_epoch
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| YOLOv5-N | CSPDarkNet-N | 640 | 250 | | | | 7.7 | 2.4 | |
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| YOLOv5-S | CSPDarkNet-S | 640 | 250 | | | | 27.1 | 9.0 | |
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| YOLOv5-M | CSPDarkNet-M | 640 | 250 | | | | 74.3 | 25.4 | |
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-| YOLOv5-L | CSPDarkNet-L | 640 | 250 | | | | 155.6 | 54.2 | |
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+| YOLOv5-L | CSPDarkNet-L | 640 | 250 | | 46.7 | 65.5 | 155.6 | 54.2 | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/yolov5_l_coco.pth) |
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* YOLOX:
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@@ -137,7 +137,7 @@ python train.py --cuda -d coco --root path/to/COCO -v yolov1 -bs 16 --max_epoch
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| Model | Backbone | Scale | Epoch | FPS | AP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | FLOPs<br><sup>(G) | Params<br><sup>(M) | Weight |
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|---------------|--------------------|-------|-------|-------|------------------------|-------------------|-------------------|--------------------|--------|
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-| YOLOv7-T | ELANNet-Tiny | 640 | 300 | | | | 22.9 | 8.1 | |
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+| YOLOv7-T | ELANNet-Tiny | 640 | 300 | | 38.0 | 56.8 | 22.6 | 7.9 | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/yolov7_t_coco.pth) |
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| YOLOv7-L | ELANNet-Large | 640 | 300 | | | | 144.6 | 44.0 | |
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- *All models are trained with ImageNet pretrained weight (IP). All FLOPs are measured with a 640x640 image size on COCO val2017. The FPS is measured with batch size 1 on 3090 GPU from the model inference to the NMS operation.*
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