Update app.py

app.py

@@ -1,3 +1,20 @@
+##############
+
+#Maximize CPU usage
+import multiprocessing
+import cv2
+
+# Get the number of CPU cores
+cpu_cores = multiprocessing.cpu_count()
+
+# Set OpenCV to use all available cores
+cv2.setNumThreads(cpu_cores)
+
+# Print the number of threads being used (optional)
+print(f"OpenCV using {cv2.getNumThreads()} threads out of {cpu_cores} available cores")
+
+##############
+
 
 import cv2
 import gradio as gr
@@ -189,7 +206,7 @@ def process_video(confidence_threshold=0.5, selected_classes=None, stream_url=No
 
     model = YOLO(model="yolo11n.pt")
     crossed_objects = {}
-    max_tracked_objects = 1000  # Maximum number of objects to track before clearing
+    max_tracked_objects = 100  # Maximum number of objects to track before clearing
 
     logger.info("Starting to process the stream...")
     while cap.isOpened():
@@ -199,7 +216,7 @@ def process_video(confidence_threshold=0.5, selected_classes=None, stream_url=No
             break
 
         # Perform object tracking with confidence threshold
-        results = model.track(frame, persist=True, conf=confidence_threshold)
+        results = model.track(frame, persist=True, conf=confidence_threshold,iou=0.5,max_det=50,verbose=False)
 
         if results[0].boxes.id is not None:
             track_ids = results[0].boxes.id.int().cpu().tolist()