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Parent(s):
5408b74
article
Browse files- .history/app_20220327195546.py +68 -0
- .history/app_20220327195551.py +68 -0
- .history/app_20220327195556.py +68 -0
- app.py +3 -1
.history/app_20220327195546.py
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import os
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os.system("pip install gfpgan")
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#os.system("pip freeze")
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#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
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import random
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import gradio as gr
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from PIL import Image
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import torch
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Abraham_Lincoln_O-77_matte_collodion_print.jpg/1024px-Abraham_Lincoln_O-77_matte_collodion_print.jpg', 'lincoln.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/a9/Henry_Ford_1888.jpg/1024px-Henry_Ford_1888.jpg', 'Henry.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/0/06/Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg/800px-Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg', 'Frida.jpg')
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import cv2
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import glob
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import numpy as np
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from basicsr.utils import imwrite
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from gfpgan import GFPGANer
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bg_upsampler = None
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# set up GFPGAN restorer
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restorer = GFPGANer(
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model_path='experiments/pretrained_models/GFPGANv1.3.pth',
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upscale=2,
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arch='clean',
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channel_multiplier=2,
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bg_upsampler=bg_upsampler)
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def inference(img):
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input_img = cv2.imread(img, cv2.IMREAD_COLOR)
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cropped_faces, restored_faces, restored_img = restorer.enhance(
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input_img, has_aligned=False, only_center_face=False, paste_back=True)
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#return Image.fromarray(restored_faces[0][:,:,::-1])
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return Image.fromarray(restored_img[:, :, ::-1])
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title = "让美好回忆更清晰"
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description = "上传老照片,点击Submit,稍等片刻,右侧Output将照片另存为即可。"
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article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'本项目克隆自akhaliq`@huggingface</a> </p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'论文地址 By 腾讯PCG</a> | <a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'本项目克隆自akhaliq`@huggingface</a> | <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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gr.Interface(
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inference,
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[gr.inputs.Image(type="filepath", 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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examples=[
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['lincoln.jpg'],
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['einstein.png'],
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['edison.jpg'],
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['Henry.jpg'],
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['Frida.jpg']
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]
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).launch(enable_queue=True,cache_examples=True,share=True)
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.history/app_20220327195551.py
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import os
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os.system("pip install gfpgan")
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#os.system("pip freeze")
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#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
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import random
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import gradio as gr
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from PIL import Image
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import torch
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Abraham_Lincoln_O-77_matte_collodion_print.jpg/1024px-Abraham_Lincoln_O-77_matte_collodion_print.jpg', 'lincoln.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/a9/Henry_Ford_1888.jpg/1024px-Henry_Ford_1888.jpg', 'Henry.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/0/06/Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg/800px-Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg', 'Frida.jpg')
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import cv2
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import glob
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import numpy as np
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from basicsr.utils import imwrite
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from gfpgan import GFPGANer
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bg_upsampler = None
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# set up GFPGAN restorer
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restorer = GFPGANer(
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model_path='experiments/pretrained_models/GFPGANv1.3.pth',
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upscale=2,
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arch='clean',
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channel_multiplier=2,
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bg_upsampler=bg_upsampler)
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def inference(img):
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input_img = cv2.imread(img, cv2.IMREAD_COLOR)
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cropped_faces, restored_faces, restored_img = restorer.enhance(
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input_img, has_aligned=False, only_center_face=False, paste_back=True)
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#return Image.fromarray(restored_faces[0][:,:,::-1])
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return Image.fromarray(restored_img[:, :, ::-1])
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title = "让美好回忆更清晰"
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description = "上传老照片,点击Submit,稍等片刻,右侧Output将照片另存为即可。"
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article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'本项目克隆自akhaliq`@huggingface</a> </p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'论文地址 By 腾讯PCG</a> | <a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'本项目克隆自akhaliq`@huggingface</a> | <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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gr.Interface(
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inference,
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[gr.inputs.Image(type="filepath", 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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examples=[
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['lincoln.jpg'],
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['einstein.png'],
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['edison.jpg'],
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['Henry.jpg'],
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['Frida.jpg']
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]
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).launch(enable_queue=True,cache_examples=True,share=True)
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.history/app_20220327195556.py
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import os
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os.system("pip install gfpgan")
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+
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4 |
+
#os.system("pip freeze")
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5 |
+
#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
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+
import random
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+
import gradio as gr
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8 |
+
from PIL import Image
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9 |
+
import torch
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10 |
+
# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Abraham_Lincoln_O-77_matte_collodion_print.jpg/1024px-Abraham_Lincoln_O-77_matte_collodion_print.jpg', 'lincoln.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
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+
# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/a/a9/Henry_Ford_1888.jpg/1024px-Henry_Ford_1888.jpg', 'Henry.jpg')
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# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/0/06/Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg/800px-Frida_Kahlo%2C_by_Guillermo_Kahlo.jpg', 'Frida.jpg')
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import cv2
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import glob
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import numpy as np
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from basicsr.utils import imwrite
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21 |
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from gfpgan import GFPGANer
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+
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+
bg_upsampler = None
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+
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+
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+
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+
# set up GFPGAN restorer
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restorer = GFPGANer(
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model_path='experiments/pretrained_models/GFPGANv1.3.pth',
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upscale=2,
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arch='clean',
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channel_multiplier=2,
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bg_upsampler=bg_upsampler)
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def inference(img):
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input_img = cv2.imread(img, cv2.IMREAD_COLOR)
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cropped_faces, restored_faces, restored_img = restorer.enhance(
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input_img, has_aligned=False, only_center_face=False, paste_back=True)
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#return Image.fromarray(restored_faces[0][:,:,::-1])
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return Image.fromarray(restored_img[:, :, ::-1])
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title = "让美好回忆更清晰"
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+
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+
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description = "上传老照片,点击Submit,稍等片刻,右侧Output将照片另存为即可。"
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article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'本项目克隆自akhaliq`@huggingface</a> </p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'论文地址 By 腾讯PCG</a> | <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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gr.Interface(
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inference,
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[gr.inputs.Image(type="filepath", 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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examples=[
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['lincoln.jpg'],
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['einstein.png'],
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['edison.jpg'],
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['Henry.jpg'],
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['Frida.jpg']
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]
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).launch(enable_queue=True,cache_examples=True,share=True)
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app.py
CHANGED
@@ -45,7 +45,9 @@ title = "让美好回忆更清晰"
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description = "上传老照片,点击Submit,稍等片刻,右侧Output将照片另存为即可。"
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article = "<p style='text-align: center'><a href='https://
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gr.Interface(
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inference,
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description = "上传老照片,点击Submit,稍等片刻,右侧Output将照片另存为即可。"
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48 |
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article = "<p style='text-align: center'><a href='https://huggingface.co/spaces/akhaliq/GFPGAN/' target='_blank'本项目克隆自akhaliq`@huggingface</a> </p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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+
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'论文地址 By 腾讯PCG</a> | <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>"
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gr.Interface(
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inference,
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