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update README.md.
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README.md

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### Quick Inference
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##### Download Pre-trained Models:
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Download the facelib pretrained models from [[Google Drive](https://drive.google.com/drive/folders/1b_3qwrzY_kTQh0-SnBoGBgOrJ_PLZSKm?usp=sharing) | [OneDrive](https://entuedu-my.sharepoint.com/:f:/g/personal/s200094_e_ntu_edu_sg/EvDxR7FcAbZMp_MA9ouq7aQB8XTppMb3-T0uGZ_2anI2mg?e=DXsJFo)] to the `weights/facelib` folder.
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You can download by run the following command OR manually download the pretrained models.
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Download the facelib pretrained models from [[Google Drive](https://drive.google.com/drive/folders/1b_3qwrzY_kTQh0-SnBoGBgOrJ_PLZSKm?usp=sharing) | [OneDrive](https://entuedu-my.sharepoint.com/:f:/g/personal/s200094_e_ntu_edu_sg/EvDxR7FcAbZMp_MA9ouq7aQB8XTppMb3-T0uGZ_2anI2mg?e=DXsJFo)] to the `weights/facelib` folder. You can manually download the pretrained models OR download by runing the following command.
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```
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python scripts/download_pretrained_models.py facelib
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```
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Download the CodeFormer pretrained models from [[Google Drive](https://drive.google.com/drive/folders/1CNNByjHDFt0b95q54yMVp6Ifo5iuU6QS?usp=sharing) | [OneDrive](https://entuedu-my.sharepoint.com/:f:/g/personal/s200094_e_ntu_edu_sg/EoKFj4wo8cdIn2-TY2IV6CYBhZ0pIG4kUOeHdPR_A5nlbg?e=AO8UN9)] to the `weights/CodeFormer` folder.
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You can download by run the following command OR manually download the pretrained models.
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Download the CodeFormer pretrained models from [[Google Drive](https://drive.google.com/drive/folders/1CNNByjHDFt0b95q54yMVp6Ifo5iuU6QS?usp=sharing) | [OneDrive](https://entuedu-my.sharepoint.com/:f:/g/personal/s200094_e_ntu_edu_sg/EoKFj4wo8cdIn2-TY2IV6CYBhZ0pIG4kUOeHdPR_A5nlbg?e=AO8UN9)] to the `weights/CodeFormer` folder. You can manually download the pretrained models OR download by runing the following command.
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```
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python scripts/download_pretrained_models.py CodeFormer
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```

inference_codeformer.py

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net.load_state_dict(checkpoint)
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net.eval()
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# ------------------ set up FaceRestoreHelper -------------------
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# large det_model: 'YOLOv5l', 'retinaface_resnet50'
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# small det_model: 'YOLOv5n', 'retinaface_mobile0.25'
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face_helper = FaceRestoreHelper(
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use_parse=True,
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device=device)
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# face_helper.init_dlib(args.detection_path, args.landmark5_path, args.landmark68_path)
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# -------------------- start to processing ---------------------
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# scan all the jpg and png images
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for img_path in sorted(glob.glob(os.path.join(args.test_path, '*.[jp][pn]g'))):
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# clean all the intermediate results to process the next image

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