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from run import process |
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import time |
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import subprocess |
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import os |
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import argparse |
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import cv2 |
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import sys |
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from PIL import Image |
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import torch |
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import gradio as gr |
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TESTdevice = "cpu" |
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index = 1 |
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""" |
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main.py |
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How to run: |
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python main.py |
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""" |
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def mainTest(inputpath, outpath): |
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watermark = deep_nude_process(inputpath) |
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return watermark |
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def deep_nude_process(item): |
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dress = (item) |
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h = dress.shape[0] |
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w = dress.shape[1] |
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dress = cv2.resize(dress, (512, 512), interpolation=cv2.INTER_CUBIC) |
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watermark = process(dress) |
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watermark = cv2.resize(watermark, (w, h), interpolation=cv2.INTER_CUBIC) |
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return watermark |
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def inference(img): |
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global index |
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outputpath = "out_" + str(index) + ".jpg" |
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index += 1 |
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print(time.strftime("START!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime())) |
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output = mainTest(img, outputpath) |
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print(time.strftime("FINISH!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime())) |
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return output |
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title = "AI脱衣" |
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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" |
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examples = [ |
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['input.png', '测试图'], |
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] |
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web = gr.Interface(inference, |
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inputs="image", |
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outputs="image", |
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title=title, |
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description=description, |
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examples=examples, |
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) |
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if __name__ == '__main__': |
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web.launch( |
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share=True, |
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enable_queue=True |
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) |
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