undress / app.py
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from run import process
import time
import subprocess
import os
import argparse
import cv2
import sys
from PIL import Image
import torch
import gradio as gr
TESTdevice = "cpu"
index = 1
"""
main.py
How to run:
python main.py
"""
def mainTest(inputpath, outpath):
watermark = deep_nude_process(inputpath)
#cv2.imwrite(outpath, watermark)
return watermark
#
def deep_nude_process(item):
# print('Processing {}'.format(item))
# dress = cv2.imread(item)
dress = (item)
h = dress.shape[0]
w = dress.shape[1]
dress = cv2.resize(dress, (512, 512), interpolation=cv2.INTER_CUBIC)
watermark = process(dress)
watermark = cv2.resize(watermark, (w, h), interpolation=cv2.INTER_CUBIC)
return watermark
def inference(img):
global index
# inputpath = "input/" + str(index) + ".jpg"
outputpath = "out_" + str(index) + ".jpg"
# cv2.imwrite(inputpath, img)
index += 1
print(time.strftime("START!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
output = mainTest(img, outputpath)
print(time.strftime("FINISH!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
return output
title = "AI脱衣"
description = "传入人物照片,类似最下方测试图的那种,将制作脱衣图,一张图至少等40秒,别传私人照片,禁止传真人照片"
examples = [
['input.png', '测试图'],
]
web = gr.Interface(inference,
inputs="image",
outputs="image",
title=title,
description=description,
examples=examples,
)
if __name__ == '__main__':
web.launch(
share=True,
enable_queue=True
)