app.py

import os
import glob

if len(glob.glob('weights/*.pth')) != 6:
    os.system('wget -q "https://public-vigen-video.oss-cn-shanghai.aliyuncs.com/robin/models/RetinaFace-R50.pth?OSSAccessKeyId=LTAI4G6bfnyW4TA4wFUXTYBe&Expires=1961116085&Signature=GlUNW6%2B8FxvxWmE9jKIZYOOciKQ%3D" -O weights/RetinaFace-R50.pth')
    os.system('wget -q "https://public-vigen-video.oss-cn-shanghai.aliyuncs.com/robin/models/GPEN-BFR-512.pth?OSSAccessKeyId=LTAI4G6bfnyW4TA4wFUXTYBe&Expires=1961116208&Signature=hBgvVvKVSNGeXqT8glG%2Bd2t2OKc%3D" -O weights/GPEN-512.pth')
    os.system('wget -q "https://public-vigen-video.oss-cn-shanghai.aliyuncs.com/robin/models/GPEN-Colorization-1024.pth?OSSAccessKeyId=LTAI4G6bfnyW4TA4wFUXTYBe&Expires=1961116315&Signature=9tPavW2h%2F1LhIKiXj73sTQoWqcc%3D" -O weights/GPEN-1024-Color.pth ')
    os.system('wget -q "https://public-vigen-video.oss-cn-shanghai.aliyuncs.com/robin/models/realesrnet_x2.pth?OSSAccessKeyId=LTAI4G6bfnyW4TA4wFUXTYBe&Expires=1962694780&Signature=lI%2FolhA%2FyigiTRvoDIVbtMIyhjI%3D" -O weights/realesrnet_x2.pth ')
    os.system('wget -q "https://public-vigen-video.oss-cn-shanghai.aliyuncs.com/robin/models/GPEN-Inpainting-1024.pth?OSSAccessKeyId=LTAI4G6bfnyW4TA4wFUXTYBe&Expires=1961116338&Signature=tvYhdLaLgW7UdcUrApXp2jsek8w%3D" -O weights/GPEN-Inpainting-1024.pth ')
    jksp = os.environ['GPEN-BFR-2048']
    os.system(f'wget -q "{jksp}" -O weights/GPEN-BFR-2048.pth')

import gradio as gr

'''
@paper: GAN Prior Embedded Network for Blind Face Restoration in the Wild (CVPR2021)
@author: yangxy (yangtao9009@gmail.com)
'''
import os
import cv2
import glob
from face_enhancement import FaceEnhancement 
from face_colorization import FaceColorization 
from face_inpainting import FaceInpainting 


def inference(file, mode):
    
    im_orig = cv2.imread(file, cv2.IMREAD_COLOR)
    im = cv2.resize(im_orig, (0,0), fx=2, fy=2)
    faceenhancer = FaceEnhancement(size=512, model='GPEN-512', channel_multiplier=2, device='cpu', u=False)
    img, orig_faces, enhanced_faces = faceenhancer.process(im)
    cv2.imwrite(os.path.join("e.png"), img)
    
    if mode == "enhance":
        return os.path.join("e.png")
    elif mode == "colorize":
        model = {'name':'GPEN-1024-Color', 'size':1024}
        grayf = cv2.imread(file, cv2.IMREAD_GRAYSCALE)
        grayf = cv2.cvtColor(grayf, cv2.COLOR_GRAY2BGR) # channel: 1->3
        facecolorizer = FaceColorization(size=model['size'], model=model['name'], channel_multiplier=2, device='cpu')
        colorf = facecolorizer.process(grayf)
        colorf = cv2.resize(colorf, (grayf.shape[1], grayf.shape[0]))
        cv2.imwrite(os.path.join("output.png"), colorf)
        return os.path.join("output.png")
    elif mode == "inpainting":
        model = {'name':'GPEN-Inpainting-1024', 'size':1024}
        faceinpainter = FaceInpainting(size=model['size'], model=model['name'], channel_multiplier=2, device='cpu')
        inpaint = faceinpainter.process(im_orig)
        cv2.imwrite(os.path.join("output.png"), inpaint)
        return os.path.join("output.png")
    elif mode == "selfie":
        model = {'name':'GPEN-BFR-2048', 'size':2048}
        im = cv2.resize(im, (0,0), fx=4, fy=4)
        faceenhancer = FaceEnhancement(size=model['size'], model=model['name'], channel_multiplier=2, device='cpu')
        img, orig_faces, enhanced_faces = faceenhancer.process(im)
        cv2.imwrite(os.path.join("output.png"), img)
        return os.path.join("output.png")
    else:
        faceenhancer = FaceEnhancement(size=512, model='GPEN-512', channel_multiplier=2, device='cpu', u=True)
        img, orig_faces, enhanced_faces = faceenhancer.process(im)
        cv2.imwrite(os.path.join("output.png"), img)
        return os.path.join("output.png")
        
        
title = "GPEN"
description = "Gradio demo for GAN Prior Embedded Network for Blind Face Restoration in the Wild. This version of gradio demo includes face colorization from GPEN. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."

article = "<p style='text-align: center;'><a href='https://arxiv.org/abs/2105.06070' target='_blank'>GAN Prior Embedded Network for Blind Face Restoration in the Wild</a> | <a href='https://github.com/yangxy/GPEN' target='_blank'>Github Repo</a></p><p style='text-align: center;'><img src='https://img.shields.io/badge/Hugging%20Face-Original%20demo-blue' alt='https://huggingface.co/spaces/akhaliq/GPEN' width='172' height='20' /></p>"


gr.Interface(
    inference, 
    [gr.inputs.Image(type="filepath", label="Input"),gr.inputs.Radio(["enhance", "colorize", "inpainting", "selfie", "enhanced+background"], type="value", default="enhance", label="Type")], 
    gr.outputs.Image(type="file", label="Output"),
    title=title,
    description=description,
    article=article,
    examples=[
    ['enhance.png', 'enhance'],
    ['color.png', 'colorize'],
    ['inpainting.png', 'inpainting'],
    ['selfie.png', 'selfie']
    ],
    enable_queue=True
).launch()