Update app.py

app.py

@@ -1,51 +1,25 @@
-'''
 import gradio as gr
-from utils import extract_frames
 from model import predict_defect
-
-def analyze_video(video):
-    frames = extract_frames(video)
-    results = [predict_defect(frame) for frame in frames]
-    return results
-
-demo = gr.Interface(
-    fn=analyze_video,
-    inputs=gr.Video(label="Upload Drone Video"),
-    outputs=gr.Gallery(label="Detected Road Defects")
-,
-    title="Drone-based Road Defect Detection",
-    description="Upload drone footage to identify and highlight road surface defects."
-)
-
-if __name__ == "__main__":
-    demo.launch()
-'''
-
-import gradio as gr
-import os
 from utils import extract_frames
-from model import predict_defect
+import os
 
-# === 1. Load videos from the Data folder ===
 DATA_DIR = "Data"
 
 def get_video_choices():
     return [os.path.join(DATA_DIR, f) for f in os.listdir(DATA_DIR) if f.endswith(".mp4")]
 
-# === 2. Analyze selected video ===
 def analyze_selected_video(video_path):
     frames = extract_frames(video_path)
     results = [predict_defect(frame) for frame in frames]
     return results
 
-# === 3. Gradio interface ===
 demo = gr.Interface(
     fn=analyze_selected_video,
-    inputs=gr.Dropdown(choices=get_video_choices(), label="Select Drone Video"),
+    inputs=gr.Dropdown(choices=lambda: get_video_choices(), label="Select Drone Video"),
     outputs=gr.Gallery(label="Detected Road Defects"),
     title="Drone-based Road Defect Detection",
-    description="Select footage from the Data folder to highlight road surface defects."
+    description="Highlight road defects (cracks, potholes, misalignments) in red using video frames."
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()