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@@ -105,11 +105,11 @@ python train.py --cuda -d coco --root path/to/COCO -v yolov1 -bs 16 --max_epoch
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| YOLOv3 | DarkNet-53 | 640 | √ | 250 | | 42.9 | 63.5 | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/yolov3_coco.pth) |
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| YOLOv4 | CSPDarkNet-53 | 640 | √ | 250 | | | | |
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| YOLOv5 | CSPDarkNet-L | 640 | √ | 250 | | | | |
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-| YOLOX | CSPDarkNet-L | 640 | √ | 300 | | | | |
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-| YOLOv7-Nano | ELANNet-Nano | 640 | √ | 300 | | | | |
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-| YOLOv7-Tiny | ELANNet-Tiny | 640 | √ | 300 | | | | |
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-| YOLOv7-Large | ELANNet-Large | 640 | √ | 300 | | | | |
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-| YOLOv7-Huge | ELANNet-Huge | 640 | √ | 300 | | | | |
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+| YOLOX | CSPDarkNet-L | 640 | √ | 250 | | 46.6 | 66.1 | |
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+| YOLOv7-Nano | ELANNet-Nano | 640 | √ | 250 | | | | |
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+| YOLOv7-Tiny | ELANNet-Tiny | 640 | √ | 250 | | | | |
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+| YOLOv7-Large | ELANNet-Large | 640 | √ | 250 | | | | |
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+| YOLOv7-Huge | ELANNet-Huge | 640 | √ | 250 | | | | |
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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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@@ -143,7 +143,7 @@ python train.py \
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-d coco \
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-v yolov1 \
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-bs 16 \
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- --max_epoch 300 \
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+ --max_epoch 250 \
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--wp_epoch 3 \
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--eval_epoch 10 \
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--ema \
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