Update app.py

app.py

@@ -42,22 +42,22 @@ SUBSAMPLE = 2
 def stream_object_detection(video, conf_threshold):
     cap = cv2.VideoCapture(video)
 
-    fps = int(cap.get(cv2.CAP_PROP_FPS))
+    #fps = int(cap.get(cv2.CAP_PROP_FPS))
 
     iterating = True
-    desired_fps = fps // SUBSAMPLE
-    batch = []
-    width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) // 2
-    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) // 2
-    n_frames = 0
+    #desired_fps = fps // SUBSAMPLE
+    #batch = []
+    #width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) // 2
+    #height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) // 2
+    #n_frames = 0
 
     while iterating:
         iterating, frame = cap.read()
         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 n_frames % SUBSAMPLE == 0:
+        batch.append(frame)
+        if len(batch) == fps:
             inputs = image_processor(images=batch, return_tensors="pt").to("cuda")
 
             print(f"starting batch of size {len(batch)}")