mirror of https://github.com/open-mmlab/mmyolo.git
fix docs of get_started.md
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6813e3e36d
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@ -190,6 +190,8 @@ def main(args):
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visualizer.show(shown_imgs)
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# Please refer to the usage tutorial:
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# https://github.com/open-mmlab/mmyolo/blob/main/docs/zh_cn/user_guides/visualization.md # noqa
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if __name__ == '__main__':
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args = parse_args()
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main(args)
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@ -74,7 +74,7 @@ To verify whether MMYOLO is installed correctly, we provide some sample codes to
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**Step 1.** We need to download config and checkpoint files.
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```shell
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mim download mmyolo --config configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco --dest .
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mim download mmyolo --config yolov5_s-v61_syncbn_fast_8xb16-300e_coco --dest .
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```
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The downloading will take several seconds or more, depending on your network environment. When it is done, you will find two files `yolov5_s-v61_syncbn_8xb16-300e_coco.py` and `yolov5_s-v61_syncbn_fast_8xb16-300e_coco_20220918_084700-86e02187.pth` in your current folder.
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@ -73,7 +73,7 @@ mim install "mmyolo"
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**步骤 1.** 我们需要下载配置文件和模型权重文件。
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```shell
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mim download mmyolo --config configs/yolov5/yolov5_s-v61_syncbn_fast_8xb16-300e_coco --dest .
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mim download mmyolo --config yolov5_s-v61_syncbn_fast_8xb16-300e_coco --dest .
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```
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载将需要几秒钟或更长时间,这取决于你的网络环境。完成后,你会在当前文件夹中发现两个文件 `yolov5_s-v61_syncbn_fast_8xb16-300e_coco.py` and `yolov5_s-v61_syncbn_fast_8xb16-300e_coco_20220918_084700-86e02187.pth`
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