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Duplicate from Xintao/GFPGAN

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Co-authored-by: Xintao Wang <[email protected]>

Files changed (5) hide show
  1. .gitattributes +31 -0
  2. README.md +14 -0
  3. app.py +151 -0
  4. packages.txt +3 -0
  5. requirements.txt +13 -0
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ title: GFPGAN
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+ emoji: 😁
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+ colorFrom: yellow
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+ colorTo: green
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+ sdk: gradio
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+ sdk_version: 3.1.7
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+ app_file: app.py
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+ pinned: false
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+ license: apache-2.0
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+ duplicated_from: Xintao/GFPGAN
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py ADDED
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+ import os
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+
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+ import cv2
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+ import gradio as gr
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+ import torch
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+ from basicsr.archs.srvgg_arch import SRVGGNetCompact
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+ from gfpgan.utils import GFPGANer
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+ from realesrgan.utils import RealESRGANer
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+
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+ os.system("pip freeze")
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+ # download weights
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+ if not os.path.exists('realesr-general-x4v3.pth'):
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+ os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth -P .")
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+ if not os.path.exists('GFPGANv1.2.pth'):
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+ os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.2.pth -P .")
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+ if not os.path.exists('GFPGANv1.3.pth'):
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+ os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth -P .")
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+ if not os.path.exists('GFPGANv1.4.pth'):
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+ os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P .")
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+ if not os.path.exists('RestoreFormer.pth'):
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+ os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth -P .")
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+ if not os.path.exists('CodeFormer.pth'):
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+ os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/CodeFormer.pth -P .")
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+
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+ torch.hub.download_url_to_file(
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+ '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',
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+ 'lincoln.jpg')
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+ torch.hub.download_url_to_file(
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+ 'https://user-images.githubusercontent.com/17445847/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg',
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+ 'AI-generate.jpg')
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+ torch.hub.download_url_to_file(
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+ 'https://user-images.githubusercontent.com/17445847/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg',
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+ 'Blake_Lively.jpg')
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+ torch.hub.download_url_to_file(
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+ 'https://user-images.githubusercontent.com/17445847/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png',
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+ '10045.png')
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+
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+ # background enhancer with RealESRGAN
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+ model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
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+ model_path = 'realesr-general-x4v3.pth'
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+ half = True if torch.cuda.is_available() else False
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+ upsampler = RealESRGANer(scale=4, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=half)
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+
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+ os.makedirs('output', exist_ok=True)
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+
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+
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+ # def inference(img, version, scale, weight):
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+ def inference(img, version, scale):
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+ # weight /= 100
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+ print(img, version, scale)
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+ if scale > 4:
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+ scale = 4 # avoid too large scale value
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+ try:
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+ extension = os.path.splitext(os.path.basename(str(img)))[1]
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+ img = cv2.imread(img, cv2.IMREAD_UNCHANGED)
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+ if len(img.shape) == 3 and img.shape[2] == 4:
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+ img_mode = 'RGBA'
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+ elif len(img.shape) == 2: # for gray inputs
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+ img_mode = None
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+ img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
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+ else:
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+ img_mode = None
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+
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+ h, w = img.shape[0:2]
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+ if h > 3500 or w > 3500:
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+ print('too large size')
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+ return None, None
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+
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+ if h < 300:
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+ img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)
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+
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+ if version == 'v1.2':
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+ face_enhancer = GFPGANer(
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+ model_path='GFPGANv1.2.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
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+ elif version == 'v1.3':
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+ face_enhancer = GFPGANer(
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+ model_path='GFPGANv1.3.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
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+ elif version == 'v1.4':
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+ face_enhancer = GFPGANer(
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+ model_path='GFPGANv1.4.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
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+ elif version == 'RestoreFormer':
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+ face_enhancer = GFPGANer(
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+ model_path='RestoreFormer.pth', upscale=2, arch='RestoreFormer', channel_multiplier=2, bg_upsampler=upsampler)
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+ # elif version == 'CodeFormer':
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+ # face_enhancer = GFPGANer(
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+ # model_path='CodeFormer.pth', upscale=2, arch='CodeFormer', channel_multiplier=2, bg_upsampler=upsampler)
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+
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+ try:
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+ # _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True, weight=weight)
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+ _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
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+ except RuntimeError as error:
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+ print('Error', error)
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+
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+ try:
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+ if scale != 2:
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+ interpolation = cv2.INTER_AREA if scale < 2 else cv2.INTER_LANCZOS4
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+ h, w = img.shape[0:2]
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+ output = cv2.resize(output, (int(w * scale / 2), int(h * scale / 2)), interpolation=interpolation)
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+ except Exception as error:
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+ print('wrong scale input.', error)
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+ if img_mode == 'RGBA': # RGBA images should be saved in png format
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+ extension = 'png'
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+ else:
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+ extension = 'jpg'
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+ save_path = f'output/out.{extension}'
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+ cv2.imwrite(save_path, output)
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+
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+ output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
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+ return output, save_path
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+ except Exception as error:
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+ print('global exception', error)
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+ return None, None
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+
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+
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+ title = "GFPGAN: Practical Face Restoration Algorithm"
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+ description = r"""Gradio demo for <a href='https://github.com/TencentARC/GFPGAN' target='_blank'><b>GFPGAN: Towards Real-World Blind Face Restoration with Generative Facial Prior</b></a>.<br>
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+ It can be used to restore your **old photos** or improve **AI-generated faces**.<br>
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+ To use it, simply upload your image.<br>
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+ If GFPGAN is helpful, please help to ⭐ the <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a> and recommend it to your friends 😊
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+ """
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+ article = r"""
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+
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+ [![download](https://img.shields.io/github/downloads/TencentARC/GFPGAN/total.svg)](https://github.com/TencentARC/GFPGAN/releases)
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+ [![GitHub Stars](https://img.shields.io/github/stars/TencentARC/GFPGAN?style=social)](https://github.com/TencentARC/GFPGAN)
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+ [![arXiv](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/abs/2101.04061)
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+
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+ If you have any question, please email 📧 `[email protected]` or `[email protected]`.
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+
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+ <center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>
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+ <center><img src='https://visitor-badge.glitch.me/badge?page_id=Gradio_Xintao_GFPGAN' alt='visitor badge'></center>
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+ """
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+ demo = gr.Interface(
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+ inference, [
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+ gr.inputs.Image(type="filepath", label="Input"),
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+ # gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'], type="value", default='v1.4', label='version'),
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+ gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer'], type="value", default='v1.4', label='version'),
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+ gr.inputs.Number(label="Rescaling factor", default=2),
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+ # gr.Slider(0, 100, label='Weight, only for CodeFormer. 0 for better quality, 100 for better identity', default=50)
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+ ], [
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+ gr.outputs.Image(type="numpy", label="Output (The whole image)"),
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+ gr.outputs.File(label="Download the output image")
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+ ],
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+ title=title,
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+ description=description,
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+ article=article,
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+ # examples=[['AI-generate.jpg', 'v1.4', 2, 50], ['lincoln.jpg', 'v1.4', 2, 50], ['Blake_Lively.jpg', 'v1.4', 2, 50],
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+ # ['10045.png', 'v1.4', 2, 50]]).launch()
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+ examples=[['AI-generate.jpg', 'v1.4', 2], ['lincoln.jpg', 'v1.4', 2], ['Blake_Lively.jpg', 'v1.4', 2],
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+ ['10045.png', 'v1.4', 2]])
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+ demo.queue(concurrency_count=1)
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+ demo.launch()
packages.txt ADDED
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+ ffmpeg
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+ libsm6
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+ libxext6
requirements.txt ADDED
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+ torch>=1.7
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+ basicsr>=1.4.2
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+ facexlib>=0.2.5
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+ gfpgan>=1.3.7
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+ realesrgan>=0.2.5
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+ numpy
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+ opencv-python
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+ torchvision
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+ scipy
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+ tqdm
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+ lmdb
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+ pyyaml
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+ yapf