Delete app.py

app.py

@@ -1,142 +0,0 @@
-import os
-
-import cv2
-import gradio as gr
-import torch
-from basicsr.archs.srvgg_arch import SRVGGNetCompact
-from gfpgan.utils import GFPGANer
-from realesrgan.utils import RealESRGANer
-
-os.system("pip freeze")
-# download weights
-if not os.path.exists('realesr-general-x4v3.pth'):
-    os.system("wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth -P .")
-if not os.path.exists('GFPGANv1.2.pth'):
-    os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.2.pth -P .")
-if not os.path.exists('GFPGANv1.3.pth'):
-    os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.3.pth -P .")
-if not os.path.exists('GFPGANv1.4.pth'):
-    os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P .")
-if not os.path.exists('RestoreFormer.pth'):
-    os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/RestoreFormer.pth -P .")
-if not os.path.exists('CodeFormer.pth'):
-    os.system("wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/CodeFormer.pth -P .")
-
-torch.hub.download_url_to_file(
-    'https://thumbs.dreamstime.com/b/tower-bridge-traditional-red-bus-black-white-colors-view-to-tower-bridge-london-black-white-colors-108478942.jpg',
-    'a1.jpg')
-torch.hub.download_url_to_file(
-    'https://media.istockphoto.com/id/523514029/photo/london-skyline-b-w.jpg?s=612x612&w=0&k=20&c=kJS1BAtfqYeUDaORupj0sBPc1hpzJhBUUqEFfRnHzZ0=',
-    'a2.jpg')
-torch.hub.download_url_to_file(
-    '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',
-    'a3.jpg')
-torch.hub.download_url_to_file(
-    'https://i.pinimg.com/736x/46/96/9e/46969eb94aec2437323464804d27706d--victorian-london-victorian-era.jpg',
-    'a4.jpg')
-
-# background enhancer with RealESRGAN
-model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
-model_path = 'realesr-general-x4v3.pth'
-half = True if torch.cuda.is_available() else False
-upsampler = RealESRGANer(scale=4, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=half)
-
-os.makedirs('output', exist_ok=True)
-
-
-# def inference(img, version, scale, weight):
-def inference(img, version, scale):
-    # weight /= 100
-    print(img, version, scale)
-    try:
-        extension = os.path.splitext(os.path.basename(str(img)))[1]
-        img = cv2.imread(img, cv2.IMREAD_UNCHANGED)
-        if len(img.shape) == 3 and img.shape[2] == 4:
-            img_mode = 'RGBA'
-        elif len(img.shape) == 2:  # for gray inputs
-            img_mode = None
-            img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
-        else:
-            img_mode = None
-
-        h, w = img.shape[0:2]
-        if h < 300:
-            img = cv2.resize(img, (w * 2, h * 2), interpolation=cv2.INTER_LANCZOS4)
-
-        if version == 'v1.2':
-            face_enhancer = GFPGANer(
-            model_path='GFPGANv1.2.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
-        elif version == 'v1.3':
-            face_enhancer = GFPGANer(
-            model_path='GFPGANv1.3.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
-        elif version == 'v1.4':
-            face_enhancer = GFPGANer(
-            model_path='GFPGANv1.4.pth', upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=upsampler)
-        elif version == 'RestoreFormer':
-            face_enhancer = GFPGANer(
-            model_path='RestoreFormer.pth', upscale=2, arch='RestoreFormer', channel_multiplier=2, bg_upsampler=upsampler)
-        elif version == 'CodeFormer':
-             face_enhancer = GFPGANer(
-             model_path='CodeFormer.pth', upscale=2, arch='CodeFormer', channel_multiplier=2, bg_upsampler=upsampler)
-        elif version == 'RealESR-General-x4v3':
-             face_enhancer = GFPGANer(
-             model_path='realesr-general-x4v3.pth', upscale=2, arch='realesr-general', channel_multiplier=2, bg_upsampler=upsampler)
-
-        try:
-            # _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True, weight=weight)
-            _, _, output = face_enhancer.enhance(img, has_aligned=False, only_center_face=False, paste_back=True)
-        except RuntimeError as error:
-            print('Error', error)
-
-        try:
-            if scale != 2:
-                interpolation = cv2.INTER_AREA if scale < 2 else cv2.INTER_LANCZOS4
-                h, w = img.shape[0:2]
-                output = cv2.resize(output, (int(w * scale / 2), int(h * scale / 2)), interpolation=interpolation)
-        except Exception as error:
-            print('wrong scale input.', error)
-        if img_mode == 'RGBA':  # RGBA images should be saved in png format
-            extension = 'png'
-        else:
-            extension = 'jpg'
-        save_path = f'output/out.{extension}'
-        cv2.imwrite(save_path, output)
-
-        output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
-        return output, save_path
-    except Exception as error:
-        print('global exception', error)
-        return None, None
-
-
-title = "Image Upscaling & Restoration(esp. Face) using GFPGAN Algorithm"
-description = r"""Gradio demo for <a href='https://github.com/TencentARC/GFPGAN' target='_blank'><b>GFPGAN: Towards Real-World Blind Face Restoration and Upscalling of the image with a Generative Facial Prior</b></a>.<br>
-Practically the algorithm is used to restore your **old photos** or improve **AI-generated faces**.<br>
-To use it, simply just upload the concerned image.<br>
-"""
-article = r"""
-[![download](https://img.shields.io/github/downloads/TencentARC/GFPGAN/total.svg)](https://github.com/TencentARC/GFPGAN/releases)
-[![GitHub Stars](https://img.shields.io/github/stars/TencentARC/GFPGAN?style=social)](https://github.com/TencentARC/GFPGAN)
-[![arXiv](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/abs/2101.04061)
-<center><img src='https://visitor-badge.glitch.me/badge?page_id=dj_face_restoration_GFPGAN' alt='visitor badge'></center>
-"""
-demo = gr.Interface(
-    inference, [
-        gr.inputs.Image(type="filepath", label="Input"),
-        # gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'], type="value", default='v1.4', label='version'),
-        gr.inputs.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer','CodeFormer','RealESR-General-x4v3'], type="value", default='v1.4', label='version'),
-        gr.inputs.Number(label="Rescaling factor", default=2),
-        # gr.Slider(0, 100, label='Weight, only for CodeFormer. 0 for better quality, 100 for better identity', default=50)
-    ], [
-        gr.outputs.Image(type="numpy", label="Output (The whole image)"),
-        gr.outputs.File(label="Download the output image")
-    ],
-    title=title,
-    description=description,
-    article=article,
-    # examples=[['AI-generate.jpg', 'v1.4', 2, 50], ['lincoln.jpg', 'v1.4', 2, 50], ['Blake_Lively.jpg', 'v1.4', 2, 50],
-    #           ['10045.png', 'v1.4', 2, 50]]).launch()
-    examples=[['a1.jpg', 'v1.4', 2], ['a2.jpg', 'v1.4', 2], ['a3.jpg', 'v1.4', 2],['a4.jpg', 'v1.4', 2]])
-    
-demo.queue(concurrency_count=4)
-demo.launch()