Update app.py

app.py

@@ -6,7 +6,7 @@ import numpy as np
 from torchvision import transforms
 import os
 
-# --- 1. MODEL ARCHITECTURE (Hidden from UI) ---
+# --- 1. MODEL ARCHITECTURE ---
 class LDobjModel(nn.Module):
     def __init__(self):
         super(LDobjModel, self).__init__()
@@ -43,7 +43,7 @@ transform = transforms.Compose([
     transforms.ToTensor()
 ])
 
-# --- 3. CORE LOGIC (With Anti-Glitch Processing) ---
+# --- 3. PROCESSING LOGIC ---
 def analyze_video(input_video_path):
     if not input_video_path:
         return None
@@ -56,25 +56,21 @@ def analyze_video(input_video_path):
     raw_output = "temp_raw.mp4"
     fourcc = cv2.VideoWriter_fourcc(*'mp4v')
     out = cv2.VideoWriter(raw_output, fourcc, fps, (width, height))
-
     morph_kernel = np.ones((5, 5), np.uint8)
 
     while cap.isOpened():
         ret, frame = cap.read()
         if not ret: break
 
-        # AI Prediction
         input_img = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
         img_tensor = transform(input_img).unsqueeze(0).to(device)
         with torch.no_grad():
             pred = model(img_tensor).squeeze().numpy()
 
-        # Mask Cleaning
         mask = (pred > 0.5).astype(np.uint8)
         mask_full = cv2.resize(mask, (width, height), interpolation=cv2.INTER_NEAREST)
         mask_full = cv2.morphologyEx(mask_full, cv2.MORPH_OPEN, morph_kernel)
 
-        # Departure Alert Logic
         moments = cv2.moments(mask_full[int(height*0.75):, :])
         if moments["m00"] > 0 and abs(int(moments["m10"] / moments["m00"]) - width // 2) > (width * 0.1):
             overlay = frame.copy()
@@ -84,41 +80,41 @@ def analyze_video(input_video_path):
 
         out.write(frame)
 
-    cap.release()
-    out.release()
-    
-    # WEB OPTIMIZATION: Convert to H.264 with FastStart for smooth web playback
+    cap.release(); out.release()
     web_output = "ldobj_final.mp4"
     os.system(f"ffmpeg -y -i {raw_output} -c:v libx264 -pix_fmt yuv420p -movflags +faststart {web_output}")
-    
     return web_output
 
-# --- 4. PERFECTED FRONTEND DESIGN ---
-# Custom CSS to lock heights and prevent the "screen flicker" during loading
+# --- 4. FRONTEND DESIGN (Corrected for Gradio 6.0) ---
 custom_css = """
 #video-container { min-height: 400px; }
 .gradio-container { background-color: #f7f9fc; }
 footer { visibility: hidden; }
 """
 
-with gr.Blocks(css=custom_css, theme=gr.themes.Default(primary_hue="red")) as app:
+# Theme and CSS removed from constructor as per the warning
+with gr.Blocks() as app:
     gr.HTML("<h1 style='text-align: center; color: #d32f2f;'>🚗 LDobj Safety Interface</h1>")
     gr.HTML("<p style='text-align: center;'>AI-Powered Lane Departure Detection & Alert System</p>")
     
-    with gr.Group(): # Groups components to prevent them from jumping around
+    with gr.Group():
         with gr.Row():
             with gr.Column(scale=1):
-                video_in = gr.Video(label="Source Dashcam Feed", mirror_webcam=False)
+                # mirror_webcam argument removed to fix TypeError
+                video_in = gr.Video(label="Source Dashcam Feed")
                 run_btn = gr.Button("START AI ANALYSIS", variant="primary")
             
             with gr.Column(scale=1):
-                # We set interactive=False to make it a dedicated player
                 video_out = gr.Video(label="LDobj Alert Output", interactive=False, autoplay=True)
 
     gr.Markdown("---")
-    gr.Markdown("### How it works\n1. **Invisible Monitor:** Under normal conditions, the video remains clean.\n2. **Active Alert:** If the car drifts, the system highlights the lanes in red and triggers an on-screen warning.")
+    gr.Markdown("### How it works\n1. **Monitor:** System analyzes lanes in the background.\n2. **Active Alert:** Warnings only appear when a lane departure is detected.")
 
     run_btn.click(fn=analyze_video, inputs=video_in, outputs=video_out)
 
 if __name__ == "__main__":
-    app.launch()
+    # Theme and CSS moved here to comply with Gradio 6.0
+    app.launch(
+        theme=gr.themes.Default(primary_hue="red"),
+        css=custom_css
+    )