Update app.py

app.py

@@ -9,8 +9,11 @@ classification_model_id = "MCG-NJU/videomae-base"
 
 # Object detection model (you can replace this with a more accurate one if needed)
 object_detection_model = "yolov5s"
+
+# Parameters for frame extraction
 TARGET_FRAME_COUNT = 16
-FRAME_SIZE = (224, 224)
+FRAME_SIZE = (224, 224)  # Expected frame size for the model
+
 def analyze_video(video):
     # Extract key frames from the video using OpenCV
     frames = extract_key_frames(video)
@@ -52,9 +55,12 @@ def extract_key_frames(video):
     frames = []
     frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
     fps = int(cap.get(cv2.CAP_PROP_FPS))
+    interval = max(1, frame_count // TARGET_FRAME_COUNT)
+    
     for i in range(frame_count):
         ret, frame = cap.read()
-        if ret and i % (fps // 2) == 0:  # Extract a frame every half second
+        if ret and i % interval == 0:  # Extract frames at regular intervals
+            frame = cv2.resize(frame, FRAME_SIZE)  # Resize frame
             frames.append(frame)
     cap.release()
     return frames