Update app.py

app.py

@@ -7,14 +7,17 @@ from ultralyticsplus import YOLO, render_result
 
 #from torch import hub # Hub contains other models like FasterRCNN
 model = YOLO('ultralyticsplus/yolov8s')
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+URL = "https://www.youtube.com/watch?v=dQw4w9WgXcQ" #URL to parse
 
 # set model parameters
 model.overrides['conf'] = 0.25  # NMS confidence threshold
 model.overrides['iou'] = 0.45  # NMS IoU threshold
 model.overrides['agnostic_nms'] = False  # NMS class-agnostic
 model.overrides['max_det'] = 1000  # maximum number of detections per image
+model.to(device)
+
 
-URL = "https://www.youtube.com/watch?v=dQw4w9WgXcQ" #URL to parse
 #play = pafy.new(_URL).streams[-1] #'-1' means read the lowest quality of video.
 
 #assert play is not None # we want to make sure their is a input to read.
@@ -42,9 +45,7 @@ URL = "https://www.youtube.com/watch?v=dQw4w9WgXcQ" #URL to parse
 """
 The function below identifies the device which is availabe to make the prediction and uses it to load and infer the frame. Once it has results it will extract the labels and cordinates(Along with scores) for each object detected in the frame.
 """
-def score_frame(frame, model):
-    device = 'cuda' if torch.cuda.is_available() else 'cpu'
-    model.to(device)
+def score_frame(frame):
     frame = [torch.tensor(frame)]
     results = model(frame)
     labels = results.xyxyn[0][:, -1].numpy()