Update app.py

app.py

@@ -184,18 +184,40 @@
 
 ###
 
-import gradio as gr
-import torch
+# import gradio as gr
+# import torch
+# import cv2
+
+# # Load the YOLOv8 model
+# model = torch.hub.load('ultralytics/yolov8', 'yolov8s', trust_repo=True)
+# model.load_state_dict(torch.load('Model_IV'))
+
+# def inference(img):
+#     results = model(img)
+#     annotated_img = results.render()[0]
+#     return annotated_img
+
+# iface = gr.Interface(fn=inference, inputs="webcam", outputs="image")
+# iface.launch()
+
 import cv2
+from ultralytics import YOLO
 
-# Load the YOLOv8 model
-model = torch.hub.load('ultralytics/yolov8', 'yolov8s', trust_repo=True)
-model.load_state_dict(torch.load('Model_IV'))
+model = YOLO('Model_IV.pt')
+print(model.names)
+webcamera = cv2.VideoCapture(0)
+# webcamera.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
+# webcamera.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
+
+while True:
+    success, frame = webcamera.read()
+    
+    results = model.track(frame, conf=0.2, imgsz=480)
+    cv2.putText(frame, f"Total: {len(results[0].boxes)}", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
+    cv2.imshow("Live Camera", results[0].plot())
 
-def inference(img):
-    results = model(img)
-    annotated_img = results.render()[0]
-    return annotated_img
+    if cv2.waitKey(1) == ord('q'):
+        break
 
-iface = gr.Interface(fn=inference, inputs="webcam", outputs="image")
-iface.launch()
+webcamera.release()
+cv2.destroyAllWindows()