Update app.py

app.py

@@ -10,9 +10,9 @@ from ultralytics import YOLO
 model = torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True)
 path  = [['image_0.jpg'], ['image_1.jpg']]
 video_path = [['TresPass_Detection_1.mp4']]
-# area =  [(215, 180), (120, 75), (370, 55), (520, 140), (215, 180) ]
-area =  [(215, 180), (110, 75), (370, 55), (520, 140), (215, 180) ]
-
+# area =  [(215, 180), (110, 75), (370, 55), (520, 140), (215, 180) ]
+# area =  [(190, 180), (100, 75), (360, 55), (510, 140), (190, 180) ]
+area =  [(215, 180), (110, 80), (360, 55), (510, 140), (215, 180) ]
 # def show_preds_video(video_path):
 def show_preds_video():
     cap = cv2.VideoCapture('TresPass_Detection_1.mp4')
@@ -22,12 +22,14 @@ def show_preds_video():
         if not ret:
             break
         count += 1
-        if count % 10 != 0:
+        if count % 8 != 0:
             continue
             # frame = cv2.imread(video_path)
+
         frame=cv2.resize(frame,(1020,600))
         frame_copy = frame.copy()
-        frame=cv2.resize(frame,(1020,600))
+
+        cv2.polylines(frame_copy, [np.array(area, np.int32)], True, (0,255,0), 2) 
 
         results=model(frame)
         for index, row in results.pandas().xyxy[0].iterrows():
@@ -42,12 +44,14 @@ def show_preds_video():
 
             if ('person') in d:
                 results = cv2.pointPolygonTest(np.array(area, np.int32), ((cx,cy)), False)
+                # results = cv2.pointPolygonTest(np.array(area, np.int32), ((x2,y1)), False)
+                # results = cv2.pointPolygonTest(np.array(area, np.int32), ((x2,y2)), False)
                 if results >0:
                         cv2.rectangle(frame_copy,(x1,y1),(x2,y2),(0,0,255),2)
                         cv2.putText(frame_copy,str(d),(x1,y1),cv2.FONT_HERSHEY_SIMPLEX,1,(0,0,255),1)
-                        cv2.putText(frame_copy,str("Alert !!! Trespasser detected !!!"),(50,400),cv2.FONT_HERSHEY_PLAIN,2,(0,0,255),3)
+                        cv2.putText(frame_copy,str("Alert !!! Trespasser detected !!!"),(50,300),cv2.FONT_HERSHEY_PLAIN,2,(0,0,255),3)
 
-        cv2.polylines(frame_copy, [np.array(area, np.int32)], True, (0,255,0), 2) 
+       
 
         yield cv2.cvtColor(frame_copy, cv2.COLOR_BGR2RGB)
 
@@ -62,52 +66,14 @@ interface_video = gr.Interface(
     fn=show_preds_video,
     inputs=inputs_video,
     outputs=outputs_video,
-    title="Intrusion Detection",
+    title="Security - Trespasser monitoring  ",
     examples=video_path,
-    cache_examples=False,
+    cache_examples=True,
+
 )
 
 gr.TabbedInterface(
     [interface_video],
     # [interface_image, interface_video],
     tab_names=['Video inference']
-).queue().launch(width=200, height = 200)
-
-
-# def show_preds_image(image_path):
-#     frame = cv2.imread(image_path)
-#     frame=cv2.resize(frame,(1020,600))
-#     results=model(frame)
-#     for index, row in results.pandas().xyxy[0].iterrows():
-#         x1 = int(row['xmin'])
-#         y1 = int(row['ymin'])
-#         x2 = int(row['xmax'])
-#         y2 = int(row['ymax'])
-#         d=(row['name'])
-
-#         cx=int(x1+x2)//2
-#         cy=int(y1+y2)//2
-
-#         if ('person') in d:
-#            results = cv2.pointPolygonTest(np.array(area, np.int32), ((cx,cy)), False)
-#            if results >0:
-#                 cv2.rectangle(frame,(x1,y1),(x2,y2),(0,0,255),2)
-#                 cv2.putText(frame,str(d),(x1,y1),cv2.FONT_HERSHEY_PLAIN,1,(255,0,0),2)
-
-#     cv2.polylines(frame, [np.array(area, np.int32)], True, (0,255,0), 2) 
-#     return cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-
-# inputs_image = [
-#     gr.components.Image(type="filepath", label="Input Image"),
-# ]
-# outputs_image = [
-#     gr.components.Image(type="numpy", label="Output Image"),
-# ]
-# interface_image = gr.Interface(
-#     fn=show_preds_image,
-#     inputs=inputs_image,
-#     outputs=outputs_image,
-#     title="Parking space counter",
-#     examples=path,
-#     cache_examples=False,
-# )
+).queue().launch(width=100, height = 100)