Update app.py

app.py

@@ -14,26 +14,11 @@ ltr=["n","s","m","1","x"]
 tsk=["","-seg","-pose","-obb","-cls"]
 #yolov8s.pt
 modin=f"yolov{ver[9]}{ltr[1]}{tsk[0]}.pt"
-
-print(modin)
 model = YOLO(modin)
-
-def draw_box(image,det):
-    height, width, channels = image.shape
-    for i,ea in enumerate(det.xyxy):
-        #bbox = convert_coords(ea, width, height)
-        #print(bbox)
-        start_point = ((int(ea[0]),int(ea[1])))
-        end_point = ((int(ea[2]),int(ea[3])))
-        label = f'{det.data["class_name"][i]}'
-        font = cv2.FONT_HERSHEY_COMPLEX  # Choose a font
-        font_scale = 1
-        color = (0, 0, 255)  # Blue color
-        thickness = 1
-        text_position = (int(ea[0]), int(ea[1]) + 10)  # Adjust position as needed
-        image = cv2.rectangle(image, start_point, end_point, color, thickness)
-        cv2.putText(image, label, text_position, font, font_scale, color, thickness) 
-    return image
+annotators = ["Box","RoundBox","BoxCorner","Color",
+              "Circle","Dot","Triangle","Elipse","Halo",
+              "PercentageBar","Mask","Polygon","Label",
+              "RichLabel","Icon","Crop","Blur","Pixelate","HeatMap"]
 
 @spaces.GPU
 def stream_object_detection(video):
@@ -57,7 +42,8 @@ def stream_object_detection(video):
         detections = sv.Detections.from_ultralytics(result)
         print(detections)
 
-        box_annotator = sv.BoxAnnotator()
+        box_annotator = eval(f'sv.{annotators[11]}()')
+        
         outp = box_annotator.annotate(
           scene=frame.copy(),
           detections=detections)