Upload app.py
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app.py
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import os
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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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os.system("pip freeze")
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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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os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.2.pth -P .")
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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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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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# 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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# Use GFPGAN for face enhancement
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face_enhancer_v3 = GFPGANer(
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model_path='GFPGANv1.3.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
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face_enhancer_v2 = GFPGANer(
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model_path='GFPGANv1.2.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
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os.makedirs('output', exist_ok=True)
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def inference(img, version, scale):
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print(img, version, scale)
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try:
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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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else:
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img_mode = None
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h, w = img.shape[0:2]
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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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if version == 'v1.2':
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face_enhancer = face_enhancer_v2
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else:
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face_enhancer = face_enhancer_v3
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try:
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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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else:
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extension = 'png'
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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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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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title = "GFPGAN: Practical Face Restoration Algorithm UPDATE: Space for GFPGAN is now at <a href='https://huggingface.co/spaces/Xintao/GFPGAN' target='_blank'>https://huggingface.co/spaces/Xintao/GFPGAN</a>"
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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 β the <a href='https://github.com/TencentARC/GFPGAN' target='_blank'>Github Repo</a> and recommend it to your friends π
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"""
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article = r"""
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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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If you have any question, please email π§ `xintao.wang@outlook.com` or `xintaowang@tencent.com`.
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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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"""
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gr.Interface(
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inference, [
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gr.inputs.Image(type="filepath", label="Input"),
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gr.inputs.Radio(['v1.2', 'v1.3'], type="value", default='v1.3', label='GFPGAN version'),
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gr.inputs.Number(label="Rescaling factor", default=2)
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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', 'v1.3', 2], ['lincoln.jpg', 'v1.3', 2], ['Blake_Lively.jpg', 'v1.3', 2],
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['10045.png', 'v1.3', 2]]).launch()
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