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@@ -145,13 +145,19 @@ There are weights-file for different cfg-files (trained for MS COCO dataset): | |
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| FPS on RTX 2070 (R) and Tesla V100 (V): | ||
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| - [yolov4x-mish.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4x-mish.cfg) - 640x640 - **67.9% [email protected] (49.4% [email protected]:0.95) - 23(R) FPS / 50(V) FPS** - 221 BFlops (110 FMA) - 381 MB: [yolov4x-mish.weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4x-mish.weights) | ||
| - [yolov4-p6.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4-p6.cfg) - 1280x1280 - **72.1% [email protected] (54.0% [email protected]:0.95) - 32(V) FPS** - xxx BFlops (xxx FMA) - 487 MB: [yolov4-p6.weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-p6.weights) | ||
| - pre-trained weights for training: https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-p6.conv.289 | ||
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| - [yolov4-p5.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4-p5.cfg) - 896x896 - **70.0% [email protected] (51.6% [email protected]:0.95) - 43(V) FPS** - xxx BFlops (xxx FMA) - 271 MB: [yolov4-p5.weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-p5.weights) | ||
| - pre-trained weights for training: https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-p5.conv.232 | ||
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| - [yolov4x-mish.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4x-mish.cfg) - 640x640 - **68.5% [email protected] (50.1% [email protected]:0.95) - 23(R) FPS / 50(V) FPS** - 221 BFlops (110 FMA) - 381 MB: [yolov4x-mish.weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4x-mish.weights) | ||
| - pre-trained weights for training: https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4x-mish.conv.166 | ||
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| - [yolov4-csp.cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4-csp.cfg) - 202 MB: [yolov4-csp.weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-csp.weights) paper [Scaled Yolo v4](https://arxiv.org/abs/2011.08036) | ||
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| just change `width=` and `height=` parameters in `yolov4-csp.cfg` file and use the same `yolov4-csp.weights` file for all cases: | ||
| - `width=640 height=640` in cfg: **66.2% [email protected] (47.5% [email protected]:0.95) - 70(V) FPS** - 120 (60 FMA) BFlops | ||
| - `width=640 height=640` in cfg: **67.4% [email protected] (48.7% [email protected]:0.95) - 70(V) FPS** - 120 (60 FMA) BFlops | ||
| - `width=512 height=512` in cfg: **64.8% [email protected] (46.2% [email protected]:0.95) - 93(V) FPS** - 77 (39 FMA) BFlops | ||
| - pre-trained weights for training: https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-csp.conv.142 | ||
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