Update app.py

app.py

@@ -62,6 +62,9 @@
 
 
 # iface.launch()
+
+
+
 import gradio as gr
 import torch
 import numpy as np
@@ -73,8 +76,10 @@ import requests
 import io
 import warnings
 
+# Suppress deprecated torch warnings
 warnings.filterwarnings("ignore")
 
+# --- Load the pre-trained StyleGAN model ---
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 model_path = 'dress_model.pkl'
 
@@ -128,6 +133,39 @@ def send_to_backend(image_buffer, user_id):
             return f"❌ Upload failed: {response.status_code} - {response.text}"
 
     except Exception as e:
-       
+        return f"⚠️ Error: {str(e)}"
+
+# --- Gradio UI ---
+with gr.Blocks(title="Style Mixing for Clothing Design") as iface:
+
+    user_id_state = gr.State()
+
+    @iface.load
+    def on_load(request: gr.Request):
+        user_id = request.query_params.get('user_id', '')
+        return user_id
+
+    gr.Markdown("## Style Mixing for Clothing Design\nUpload two projected clothing images and mix their styles.")
+
+    with gr.Row():
+        image1_input = gr.Image(label="First Clothing Image", type="filepath")
+        image2_input = gr.Image(label="Second Clothing Image", type="filepath")
+
+    mix_slider = gr.Slider(label="Style Mixing Strength (Layers 0 to N)", minimum=0, maximum=9, step=1, value=5)
+
+    with gr.Row():
+        output_image = gr.Image(label="Mixed Clothing Design")
+        save_button = gr.Button("Download & Save to Database")
+
+    image_buffer = gr.State()
+    save_status = gr.Textbox(label="Save Status", interactive=False)
+
+    def mix_and_store(image1, image2, mix_value):
+        result_image, buffer = style_mixing_interface(image1, image2, mix_value)
+        return result_image, buffer
+
+    mix_slider.change(mix_and_store, inputs=[image1_input, image2_input, mix_slider], outputs=[output_image, image_buffer])
+    save_button.click(send_to_backend, inputs=[image_buffer, user_id_state], outputs=[save_status])
 
+iface.launch()