Update app.py

app.py

@@ -7,7 +7,6 @@ import sys
 from PIL import Image
 import torch
 import gradio as gr
-import urllib.parse
 
 TESTdevice = "cpu"
 index = 1
@@ -38,56 +37,49 @@ def inference(img):
     print(time.strftime("Finish!!!!!!!!! %Y-%m-%d %H:%M:%S", time.localtime()))
     return output
 
-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 init_interface(request: gr.Request):
+    query_params = request.query_params
+    bg_color = query_params.get('bg_color', 'rgb(17, 24, 39)')
+    image_height = query_params.get('image_height', '90%')
+    css = f"""
+    body {{
+        background-color: {bg_color};
+        color: white;
+        overflow: hidden;
+    }}
+    .gradio-container {{
+        background-color: {bg_color} !important;
+        border: none !important;
+    }}
+    .image-container {{
+        height: {image_height} !important;
+        display: flex;
+        align-items: center;
+        justify-content: center;
+    }}
+    .image-container img {{
+        width: auto !important;
+        height: 100% !important;
+    }}
+    footer {{
+        display: none !important;
+    }}
+    """
 
-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;
-}}
-"""
+    with gr.Blocks(css=css) as demo:
+        with gr.Column():
+            with gr.Row(elem_id="image-container"):
+                image_input = gr.Image(type="numpy", label="Upload Image")
+            process_button = gr.Button("Process Image")
 
-width, height, bg_color = parse_url_params()
-formatted_css = css.format(width=width, height=height, bg_color=bg_color)
-
-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")
-
-    def update_status(img):
-        return inference(img), gr.update(value="Processing complete!")
+        process_button.click(update_status, inputs=image_input, outputs=[image_input])
+    
+    return demo
 
-    process_button.click(update_status, inputs=image_input, outputs=[image_input])
+with gr.Blocks() as outer_demo:
+    outer_demo.load(init_interface)
 
-demo.launch()
+outer_demo.launch()