Update video_detection.py

video_detection.py

@@ -32,10 +32,11 @@ def draw_boxes(frame, results):
     return frame
     
 def video_detection(cap):
-    video_codec = cv2.VideoWriter_fourcc(*"mp4v") # type: ignore
+    #video_codec = cv2.VideoWriter_fourcc(*"mp4v") # type: ignore
+    video_codec = cv2.VideoWriter_fourcc(*'h264')
     fps = int(cap.get(cv2.CAP_PROP_FPS))
 
-    desired_fps = fps // SUBSAMPLE
+    #desired_fps = fps // SUBSAMPLE
     width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) // 2
     height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) // 2
 
@@ -44,14 +45,15 @@ def video_detection(cap):
     n_frames = 0
 
     name = f"output_{uuid.uuid4()}.mp4"
-    segment_file = cv2.VideoWriter(name, video_codec, desired_fps, (width, height)) # type: ignore
+    segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height)) # type: ignore
     batch = []
     while iterating:
         frame = cv2.resize( frame, (0,0), fx=0.5, fy=0.5)
         #frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
         if n_frames % SUBSAMPLE == 0:
             batch.append(frame)
-        if len(batch) == 2 * desired_fps:
+        #if len(batch) == 2 * desired_fps:
+        if len(batch) == 8:
             #inputs = image_processor(images=batch, return_tensors="pt").to("cuda")
 
             print(f"starting batch of size {len(batch)}")
@@ -90,7 +92,7 @@ def video_detection(cap):
             end = time.time()
             print("time taken for processing boxes", end - start)
             name = f"output_{uuid.uuid4()}.mp4"
-            segment_file = cv2.VideoWriter(name, video_codec, desired_fps, (width, height)) # type: ignore
+            segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height)) # type: ignore
 
         iterating, frame = cap.read()
         n_frames += 1