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import os |
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import random |
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import gradio as gr |
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from PIL import Image |
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import torch |
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from random import randint |
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import sys |
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from subprocess import call |
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import psutil |
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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') |
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torch.hub.download_url_to_file('https://upload.wikimedia.org/wikipedia/commons/5/50/Albert_Einstein_%28Nobel%29.png', 'einstein.png') |
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def run_cmd(command): |
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try: |
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print(command) |
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call(command, shell=True) |
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except KeyboardInterrupt: |
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print("Process interrupted") |
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sys.exit(1) |
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run_cmd("wget https://github.com/TencentARC/GFPGAN/releases/download/v0.2.0/GFPGANCleanv1-NoCE-C2.pth -P .") |
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run_cmd("pip install basicsr") |
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run_cmd("pip install facexlib") |
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run_cmd("pip freeze") |
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def inference(img): |
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_id = randint(1, 10000) |
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INPUT_DIR = "/tmp/input_image" + str(_id) + "/" |
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OUTPUT_DIR = "/tmp/output_image" + str(_id) + "/" |
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run_cmd("rm -rf " + INPUT_DIR) |
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run_cmd("rm -rf " + OUTPUT_DIR) |
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run_cmd("mkdir " + INPUT_DIR) |
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run_cmd("mkdir " + OUTPUT_DIR) |
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basewidth = 256 |
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wpercent = (basewidth/float(img.size[0])) |
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hsize = int((float(img.size[1])*float(wpercent))) |
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img = img.resize((basewidth,hsize), Image.ANTIALIAS) |
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img.save(INPUT_DIR + "1.jpg", "JPEG") |
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run_cmd("python inference_gfpgan.py --upscale 2 --test_path "+ INPUT_DIR + " --save_root " + OUTPUT_DIR + " --paste_back") |
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return os.path.join(OUTPUT_DIR, "1_00.png") |
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title = "GFP-GAN" |
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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" |
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2101.04061'>Towards Real-World Blind Face Restoration with Generative Facial Prior</a> | <a href='https://github.com/TencentARC/GFPGAN'>Github Repo</a></p><center><img src='https://visitor-badge.glitch.me/badge?page_id=akhaliq_GFPGAN' alt='visitor badge'></center>" |
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gr.Interface( |
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inference, |
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[gr.inputs.Image(type="pil", label="Input")], |
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gr.outputs.Image(type="file", label="Output"), |
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title=title, |
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description=description, |
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article=article, |
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examples=[ |
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['lincoln.jpg'], |
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['einstein.png'] |
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], |
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enable_queue=True |
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).launch(debug=True) |
