Update app.py

app.py

@@ -1,9 +1,16 @@
-import gradio as gr
-import cv2
 import time
-from urllib.parse import parse_qs, urlparse
+import subprocess
+import os
+import argparse
+import cv2
+import sys
+from PIL import Image
+import torch
+import gradio as gr
+import urllib.parse
 
-TESTdevice = "cpu"
+TEST
+device = "cpu"
 index = 1
 
 def mainTest(inputpath, outpath):
@@ -25,7 +32,6 @@ def inference(img):
     bgra = cv2.cvtColor(img, cv2.COLOR_RGBA2BGRA)
     inputpath = f"input_{index}.jpg"
     cv2.imwrite(inputpath, bgra)
-
     outputpath = f"out_{index}.jpg"
     index += 1
     print(time.strftime("START!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
@@ -33,46 +39,56 @@ def inference(img):
     print(time.strftime("Finish!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
     return output
 
-def get_css(bg_color, width, height):
-    return f"""
-    body {{
-        background-color: {bg_color};
-        color: white;
-        overflow: hidden; /* Prevent scrolling */
-    }}
-    .gradio-container {{
-        background-color: {bg_color} !important;
-        border: none !important;
-        width: {width} !important;  /* Set the width */
-        height: {height} !important; /* Set the height */
-        max-width: 100%; /* Ensure it does not exceed the container's width */
-        max-height: 100%; /* Ensure it does not exceed the container's height */
-        overflow: hidden; /* Prevent internal scrolling */
-    }}
-    footer {{display: none !important;}} /* Hide footer */
-    """
+def parse_url_params():
+    url = os.environ.get('GRADIO_SERVER_URL', '')
+    parsed_url = urllib.parse.urlparse(url)
+    params = urllib.parse.parse_qs(parsed_url.query)
+    
+    width = params.get('width', ['auto'])[0]
+    height = params.get('height', ['100%'])[0]
+    bg_color = params.get('bg_color', ['rgb(17, 24, 39)'])[0]
+    
+    return width, height, bg_color
+
+title = "Undress AI"
+description = "⛔ 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. 🔞 Do not upload personal photos 🔞 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 ⛔"
 
-def update_status(img):
-    return inference(img), gr.update(value="Processing complete!")
+examples = [
+    ['input.png', 'Test'],
+    ['input.jpg', 'Test'],
+]
 
-def create_interface(request: gr.Request):
-    # Extract URL parameters
-    query_params = request.query_params
-    bg_color = query_params.get('bg_color', 'rgb(17, 24, 39)')
-    width = int(query_params.get('width', 'auto'))
-    height = int(query_params.get('height', '90%'))
+css = """
+body {{
+    background-color: {bg_color};
+    color: white;
+    overflow: hidden;
+}}
+.gradio-container {{
+    background-color: {bg_color} !important;
+    border: none !important;
+    width: {width} !important;
+    height: {height} !important;
+    max-width: 100%;
+    max-height: 100%;
+    overflow: hidden;
+}}
+footer {{
+    display: none !important;
+}}
+"""
 
-    css = get_css(bg_color, width, height)
+width, height, bg_color = parse_url_params()
+formatted_css = css.format(width=width, height=height, bg_color=bg_color)
 
-    with gr.Blocks(css=css) as demo:
-        with gr.Column():
-            image_input = gr.Image(type="numpy", label="Upload Image", height=height, width=width)
-            process_button = gr.Button("Process Image")
-            status = gr.Markdown(value="")
+with gr.Blocks(css=formatted_css) as demo:
+    with gr.Column():
+        image_input = gr.Image(type="numpy", label="Upload Image", height=512, width=512)
+        process_button = gr.Button("Process Image")
 
-        process_button.click(update_status, inputs=image_input, outputs=[image_input, status])
+    def update_status(img):
+        return inference(img), gr.update(value="Processing complete!")
 
-    return demo
+    process_button.click(update_status, inputs=image_input, outputs=[image_input])
 
-with gr.Blocks() as outer_demo:
-    gr.Interface(fn=create_interface).launch()
+demo.launch()