Update app.py

app.py

@@ -7,12 +7,11 @@ import tempfile
 import time
 import os
 
-# Fix Ultralytics config (HF Spaces fix)
+# Fix Ultralytics path (HF Spaces)
 os.environ["YOLO_CONFIG_DIR"] = "/tmp/Ultralytics"
 
-# 🔥 Use your trained model for real pothole detection
-# model = YOLO("best.pt")
-model = YOLO("yolov8n.pt")  # fallback demo
+# 🔥 Replace with best.pt for real pothole detection
+model = YOLO("yolov8n.pt")
 
 detections_log = []
 
@@ -34,9 +33,12 @@ def process_video(video, conf_threshold):
         if not cap.isOpened():
             return None, None, "Cannot open video", pd.DataFrame()
 
+        # 🎥 FIX FPS (avoid fast video)
         fps = cap.get(cv2.CAP_PROP_FPS)
         if fps <= 0 or fps > 60:
-            fps = 25
+            fps = 20
+
+        output_fps = max(10, fps * 0.6)
 
         width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) or 640
         height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) or 480
@@ -44,7 +46,7 @@ def process_video(video, conf_threshold):
         output_path = os.path.join(tempfile.gettempdir(), f"out_{int(time.time())}.mp4")
 
         fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-        out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
+        out = cv2.VideoWriter(output_path, fourcc, output_fps, (width, height))
 
         if not out.isOpened():
             return None, None, "VideoWriter failed", pd.DataFrame()
@@ -52,27 +54,39 @@ def process_video(video, conf_threshold):
         pothole_count = 0
         frame_count = 0
 
+        # ⚡ Frame skipping for smoother output
+        frame_skip = 2
+        frame_id = 0
+
         while cap.isOpened():
             ret, frame = cap.read()
             if not ret:
                 break
 
+            frame_id += 1
+
+            if frame_id % frame_skip != 0:
+                continue
+
             frame = cv2.resize(frame, (width, height))
+
+            # 🔧 Smooth frame
+            frame = cv2.GaussianBlur(frame, (3, 3), 0)
+
             results = model(frame)[0]
 
-            # 🔴 Detection loop
             for box in results.boxes:
                 conf = float(box.conf[0])
 
-                if conf < conf_threshold:
+                # 🎯 Better filtering
+                if conf < max(conf_threshold, 0.4):
                     continue
 
                 x1, y1, x2, y2 = map(int, box.xyxy[0])
 
-                # 🔴 RED BOUNDING BOX
+                # 🔴 RED BOX
                 cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 4)
 
-                # Label text
                 label = f"Pothole {conf:.2f}"
 
                 # Label background
@@ -118,19 +132,18 @@ def process_video(video, conf_threshold):
 # ---------------- UI ---------------- #
 with gr.Blocks() as demo:
 
-    gr.Markdown("# 🚧 Smart Pothole Detection (YOLO)")
+    gr.Markdown("# 🚧 Smart Pothole Detection (Improved)")
 
     with gr.Row():
 
-        # LEFT PANEL (SMALL)
+        # LEFT PANEL
         with gr.Column(scale=1):
             video_input = gr.Video(label="Upload Video")
-            conf = gr.Slider(0, 1, value=0.3, step=0.05, label="Confidence")
+            conf = gr.Slider(0, 1, value=0.4, step=0.05, label="Confidence")
             btn = gr.Button("Run Detection")
 
-        # RIGHT PANEL (BIG)
+        # RIGHT PANEL (BIG VIDEOS)
         with gr.Column(scale=3):
-
             with gr.Row():
                 before = gr.Video(label="Original")
                 after = gr.Video(label="Detected")
@@ -145,6 +158,6 @@ with gr.Blocks() as demo:
     )
 
 
-# HF Spaces compatible launch
+# HF Spaces launch
 if __name__ == "__main__":
     demo.launch()