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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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def mainTest(inputpath, outpath): |
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watermark = deep_nude_process(inputpath) |
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watermark1 = cv2.cvtColor(watermark, cv2.COLOR_BGRA2RGBA) |
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return watermark1 |
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def deep_nude_process(inputpath): |
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dress = cv2.imread(inputpath) |
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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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bgra = cv2.cvtColor(img, cv2.COLOR_RGBA2BGRA) |
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inputpath = f"input_{index}.jpg" |
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cv2.imwrite(inputpath, bgra) |
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outputpath = f"out_{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(inputpath, 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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from PIL import Image |
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def load_image_from_file(file_path, new_height=None): |
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""" |
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Load an image from a file and optionally resize it while maintaining the aspect ratio. |
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Args: |
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file_path (str): The path to the image file. |
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new_height (int, optional): The new height for the image. If None, the image is not resized. |
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Returns: |
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Image: The loaded (and optionally resized) image. |
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""" |
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try: |
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img = Image.open(file_path) |
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if new_height is not None: |
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aspect_ratio = img.width / img.height |
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new_width = int(new_height * aspect_ratio) |
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img = img.resize((new_width, new_height), Image.LANCZOS) |
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return img |
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except FileNotFoundError: |
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print(f"File not found: {file_path}") |
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return None |
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except Image.UnidentifiedImageError: |
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print(f"Cannot identify image file: {file_path}") |
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return None |
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except Exception as e: |
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print(f"Error loading image from file: {e}") |
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return None |
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title = "Undress AI" |
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description = "β Input photos of people, similar to the test picture at the bottom, and undress pictures will be produced. You may have to wait 30 seconds for a picture. π Do not upload personal photos π There is a queue system. According to the logic of first come, first served, only one picture will be made at a time. Must be able to at least see the outline of a human body β" |
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examples = [ |
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[load_image_from_file('example9.webp')], |
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[load_image_from_file('example2.png')], |
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[load_image_from_file('example1.png')], |
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[load_image_from_file('example5.webp')], |
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[load_image_from_file('example6.webp')], |
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[load_image_from_file('example8.webp')], |
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] |
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css = """ |
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body { |
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background-color: rgb(3, 7, 18); |
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color: white; |
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} |
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.gradio-container { |
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background-color: rgb(3, 7, 18) !important; |
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border: none !important; |
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} |
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#example_img .hide-container{ |
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height:100%; |
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width:50px; |
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transition: transform 0.5s ease; |
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} |
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#example_img{ |
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width:50px; |
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height:100%; |
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} |
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#example_img img{ |
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height:50px; |
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width:50px; |
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transition: transform 0.5s ease; |
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} |
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#example_img .container{ |
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height:50px; |
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width:50px; |
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transition: transform 0.5s ease; |
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} |
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footer {display: none !important;} |
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""" |
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js=''' |
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<script> |
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window.postMessageToParent = function(img, event, source, value) { |
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// Construct the message object with the provided parameters |
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console.log("post start",event, source, value); |
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const message = { |
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event: event, |
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source: source, |
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value: value |
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}; |
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// Post the message to the parent window |
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window.parent.postMessage(message, '*'); |
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console.log("post finish"); |
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return img; |
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} |
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</script> |
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''' |
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with gr.Blocks(css=css, head=js) as demo: |
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width=240 |
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height=340 |
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with gr.Row(): |
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with gr.Column(min_width=240,scale=3): |
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image_input = gr.Image(type="numpy", label="Upload Image", height=height) |
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process_button = gr.Button("Nude!",size="sm") |
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with gr.Column(scale=1,min_width=50): |
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gr.Examples(examples=examples, inputs=image_input, examples_per_page=10, elem_id="example_img") |
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def update_status(img): |
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processed_img = inference(img) |
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return processed_img |
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process_button.click(update_status, inputs=image_input, outputs=image_input, js='''(i) => window.postMessageToParent(i, "process_started", "demo_hf_deepnude_gan_card", "click_nude")''') |
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demo.queue(max_size=10) |
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demo.launch() |
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