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''' |
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Author: Egrt |
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Date: 2022-01-13 13:34:10 |
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LastEditors: [egrt] |
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LastEditTime: 2022-05-04 12:59:41 |
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FilePath: \MaskGAN\app.py |
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''' |
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import os |
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os.system('pip install requirements.txt') |
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from PIL import Image |
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from maskgan import MASKGAN |
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import gradio as gr |
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import os |
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maskgan = MASKGAN() |
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def inference(img): |
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lr_shape = [112, 112] |
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img = img.resize(tuple(lr_shape), Image.BICUBIC) |
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r_image = maskgan.generate_1x1_image(img) |
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return r_image |
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title = "MaskGAN:融合无监督的口罩遮挡人脸修复" |
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description = "使用生成对抗网络对口罩遮挡人脸进行修复,能够有效的恢复被遮挡区域人脸。 @西南科技大学智能控制与图像处理研究室" |
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2108.10257' target='_blank'>MaskGAN: Face Restoration Using Swin Transformer</a> | <a href='https://github.com/JingyunLiang/SwinIR' target='_blank'>Github Repo</a></p>" |
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example_img_dir = 'img' |
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example_img_name = os.listdir(example_img_dir) |
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examples=[[os.path.join(example_img_dir, image_path)] for image_path in example_img_name if image_path.endswith('.jpg')] |
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gr.Interface( |
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inference, |
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[gr.inputs.Image(type="pil", label="Input")], |
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gr.outputs.Image(type="pil", label="Output"), |
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title=title, |
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description=description, |
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article=article, |
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enable_queue=True, |
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examples=examples |
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).launch(debug=True) |
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