trysem/restoregfp
0
1import os2 3import cv24import gradio as gr5import torch6from basicsr.archs.srvgg_arch import SRVGGNetCompact7from gfpgan.utils import GFPGANer8from realesrgan.utils import RealESRGANer9 10os.system("pip freeze")11# download weights12if not os.path.exists('realesr-general-x4v3.pth'):13 os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth -P .")14if not os.path.exists('GFPGANv1.2.pth'):15 os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.2.pth -P .")16if not os.path.exists('GFPGANv1.3.pth'):17 os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth -P .")18if not os.path.exists('GFPGANv1.4.pth'):19 os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P .")20if not os.path.exists('RestoreFormer.pth'):21 os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth -P .")22if not os.path.exists('CodeFormer.pth'):23 os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/CodeFormer.pth -P .")24 25torch.hub.download_url_to_file(26 'https://thumbs.dreamstime.com/b/tower-bridge-traditional-red-bus-black-white-colors-view-to-tower-bridge-london-black-white-colors-108478942.jpg',27 'a1.jpg')28torch.hub.download_url_to_file(29 'https://media.istockphoto.com/id/523514029/photo/london-skyline-b-w.jpg?s=612x612&w=0&k=20&c=kJS1BAtfqYeUDaORupj0sBPc1hpzJhBUUqEFfRnHzZ0=',30 'a2.jpg')31torch.hub.download_url_to_file(32 'https://i.guim.co.uk/img/media/06f614065ed82ca0e917b149a32493c791619854/0_0_3648_2789/master/3648.jpg?width=700&quality=85&auto=format&fit=max&s=05764b507c18a38590090d987c8b6202',33 'a3.jpg')34torch.hub.download_url_to_file(35 'https://i.pinimg.com/736x/46/96/9e/46969eb94aec2437323464804d27706d--victorian-london-victorian-era.jpg',36 'a4.jpg')37 38# background enhancer with RealESRGAN39model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')40model_path = 'realesr-general-x4v3.pth'41half = True if torch.cuda.is_available() else False42upsampler = RealESRGANer(scale=4, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=half)43 44os.makedirs('output', exist_ok=True)45 46 47# def inference(img, version, scale, weight):48def inference(img, version, scale):49 # weight /= 10050 print(img, version, scale)51 try:52 extension = os.path.splitext(os.path.basename(str(img)))[1]53 img = cv2.imread(img, cv2.IMREAD_UNCHANGED)54 if len(img.shape) == 3 and img.shape[2] == 4:55 img_mode = 'RGBA'56 elif len(img.shape) == 2: # for gray inputs57 img_mode = None58 img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)59 else:60 img_mode = None61 62 h, w = img.shape[0:2]63 if h < 300:64 img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)65 66 if version == 'v1.2':67 face_enhancer = GFPGANer(68 model_path='GFPGANv1.2.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)69 elif version == 'v1.3':70 face_enhancer = GFPGANer(71 model_path='GFPGANv1.3.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)72 elif version == 'v1.4':73 face_enhancer = GFPGANer(74 model_path='GFPGANv1.4.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)75 elif version == 'RestoreFormer':76 face_enhancer = GFPGANer(77 model_path='RestoreFormer.pth', upscale=2, arch='RestoreFormer', channel_multiplier=2, bg_upsampler=upsampler)78 elif version == 'CodeFormer':79 face_enhancer = GFPGANer(80 model_path='CodeFormer.pth', upscale=2, arch='CodeFormer', channel_multiplier=2, bg_upsampler=upsampler)81 elif version == 'RealESR-General-x4v3':82 face_enhancer = GFPGANer(83 model_path='realesr-general-x4v3.pth', upscale=2, arch='realesr-general', channel_multiplier=2, bg_upsampler=upsampler)84 85 try:86 # _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True, weight=weight)87 _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)88 except RuntimeError as error:89 print('Error', error)90 91 try:92 if scale != 2:93 interpolation = cv2.INTER_AREA if scale < 2 else cv2.INTER_LANCZOS494 h, w = img.shape[0:2]95 output = cv2.resize(output, (int(w * scale / 2), int(h * scale / 2)), interpolation=interpolation)96 except Exception as error:97 print('wrong scale input.', error)98 if img_mode == 'RGBA': # RGBA images should be saved in png format99 extension = 'png'100 else:101 extension = 'jpg'102 save_path = f'output/out.{extension}'103 cv2.imwrite(save_path, output)104 105 output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)106 return output, save_path107 except Exception as error:108 print('global exception', error)109 return None, None110 111title = "Image Upscaling & Restoration(esp. Face)"112description = r"""113Restore your **old photos** or improve **AI-generated faces**.<br>114To use it, simply just upload the image.<br>115"""116article = r"""117 118"""119demo = gr.Interface(120 inference,[121 gr.inputs.Image(type="filepath", label="Input"),122 # gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'], type="value", default='v1.4', label='version'),123 gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer','CodeFormer','RealESR-General-x4v3'], type="value", default='v1.4', label='version'),124 gr.inputs.Number(label="Rescaling factor", default=2),125 # gr.Slider(0, 100, label='Weight, only for CodeFormer. 0 for better quality, 100 for better identity', default=50)126 ],[127 gr.outputs.Image(type="numpy", label="Output (The whole image)"),128 gr.outputs.File(label="Download the output image")129 ],130 title=title,131 description=description,132 article=article,133 css="footer {visibility: hidden}",134 # examples=[['AI-generate.jpg', 'v1.4', 2, 50], ['lincoln.jpg', 'v1.4', 2, 50], ['Blake_Lively.jpg', 'v1.4', 2, 50],135 # ['10045.png', 'v1.4', 2, 50]]).launch()136 examples=[['a1.jpg', 'v1.4', 2], ['a2.jpg', 'v1.4', 2], ['a3.jpg', 'v1.4', 2],['a4.jpg', 'v1.4', 2]])137 138demo.queue(concurrency_count=4)139demo.launch()