Add application file

.history/app_20220326215622.py

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+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='GFPGANCleanv1-NoCE-C2.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326225131.py

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+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='GFPGANCleanv1-NoCE-C2.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326225537.py

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+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='GFPGANCleanv1-NoCE-C2.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326225603.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326225611.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326225639.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326230240.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326230353.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326230358.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326230538.py

@@ -0,0 +1,68 @@
+import os
+os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326231036.py

@@ -0,0 +1,68 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326232312.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326233155.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+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')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+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')
+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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220326233250.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327000906.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001145.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-0])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001147.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-0])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001316.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001317.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001520.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001522.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001529.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001559.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001612.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327001641.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img)
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002459.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_img , restored_faces= restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002503.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_img , restored_faces= restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002645.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002649.py

@@ -0,0 +1,66 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002712.py

@@ -0,0 +1,66 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002809.py

@@ -0,0 +1,66 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002819.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327002904.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003334.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_img , restored_faces= restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_faces[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003336.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_img , restored_faces= restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003455.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_img , restored_faces= restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[1][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003506.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_img , restored_faces= restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[2][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003524.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[2][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003525.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[2][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003535.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[2][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003604.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003733.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-2])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003750.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-2])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003753.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-2])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327003759.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-3])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327004133.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327004134.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    cropped_faces, restored_faces, restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327004219.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327004403.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img)
+    restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)

.history/app_20220327004416.py

@@ -0,0 +1,65 @@
+import os
+#os.system("pip install gfpgan")
+
+#os.system("pip freeze")
+#os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .")
+import random
+import gradio as gr
+from PIL import Image
+import torch
+# 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')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png')
+# torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/thumb/9/9d/Thomas_Edison2.jpg/1024px-Thomas_Edison2.jpg', 'edison.jpg')
+# 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')
+# 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')
+
+
+
+
+import cv2
+import glob
+import numpy as np
+from basicsr.utils import imwrite
+from gfpgan import GFPGANer
+
+import warnings
+warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
+              'If you really want to use it, please modify the corresponding codes.')
+bg_upsampler = None
+
+
+ 
+# set up GFPGAN restorer
+restorer = GFPGANer(
+    model_path='experiments/pretrained_models/GFPGANv1.3.pth',
+    upscale=2,
+    arch='clean',
+    channel_multiplier=2,
+    bg_upsampler=bg_upsampler)
+
+
+def inference(img):
+    input_img = cv2.imread(img, cv2.IMREAD_COLOR)
+    restored_img = restorer.enhance(
+        input_img, has_aligned=False, only_center_face=False, paste_back=True)
+    
+    return Image.fromarray(restored_img[0][:,:,::-1])
+        
+title = "GFP-GAN"
+description = "Gradio demo for GFP-GAN: Towards Real-World Blind Face Restoration with Generative Facial Prior. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below. Please click submit only once"
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061' target='_blank'>Towards Real-World Blind Face Restoration with Generative Facial Prior</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>"
+gr.Interface(
+    inference, 
+    [gr.inputs.Image(type="filepath", label="Input")], 
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+    ['lincoln.jpg'],
+    ['einstein.png'],
+    ['edison.jpg'],
+    ['Henry.jpg'],
+    ['Frida.jpg']
+    ]
+    ).launch(enable_queue=True,cache_examples=True)