I’d successfully imported https://www.youtube.com/watch?v=hg4oVgNq7Do&t=368s detection software on VS Code. While, I now can apply Yolov8 data classification on images/videos. However, I would like to implement data classification on live video feeds.

I utilized this guide on creating a live video feed: https://www.youtube.com/watch?v=IHbJcOex6dk&t=334s. I imported supervision onto the terminal. I implemented the code suggested within this Stack Overflow Answer post: Python ModuleNotFoundError when importing custom module.

However, I am now faced with another debugging issue.

yolov8_live.py

import torch
import numpy as np
import cv2
from time import time
from ultralytics import YOLO

import supervision as sv
from supervision import Detections, BoxAnnotator

class ObjectDetection:

    def __init__(self, capture_index):
       
        self.capture_index = capture_index
        
        self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
        print("Using Device: ", self.device)
        
        self.model = self.load_model()
        
        self.CLASS_NAMES_DICT = self.model.model.names
    
        self.box_annotator = sv.BoxAnnotator(sv.ColorPalette.default(), thickness=3, text_thickness=3, text_scale=1.5)
    

    def load_model(self):
       
        model = YOLO("yolov8m.pt")  # load a pretrained YOLOv8n model
        model.fuse()
    
        return model


    def predict(self, frame):
       
        results = self.model(frame)
        
        return results
    

    def plot_bboxes(self, results, frame):
        
        xyxys = []
        confidences = []
        class_ids = []
        
         # Extract detections for person class
        for result in results:
            boxes = result.boxes.cpu().numpy()
            class_id = boxes.cls[0]
            conf = boxes.conf[0]
            xyxy = boxes.xyxy[0]

            if class_id == 0.0:
          
              xyxys.append(result.boxes.xyxy.cpu().numpy())
              confidences.append(result.boxes.conf.cpu().numpy())
              class_ids.append(result.boxes.cls.cpu().numpy().astype(int))
            
        
        # Setup detections for visualization
            detections = sv.Detections(
                            xyxy=results[0].boxes.xyxy.cpu().numpy(),
                            confidence=results[0].boxes.conf.cpu().numpy(),
                            class_id=results[0].boxes.cls.cpu().numpy().astype(int),
                        )

        # Format custom labels
        # self.labels = [f"{self.CLASS_NAMES_DICT[class_id]} {confidence:0.2f}"
         #             for _, xyxy, confidenc0e, class_id in detections]
        
        self.labels = [f"{self.CLASS_NAMES_DICT[detection.class_id] if detection.class_id else None} {detection.confidence:0.2f}"
                       for detection in detections]
        
        # Annotate and display frame
        frame = self.box_annotator.annotate(scene=frame, detections=detections, labels=self.labels)
        
        return frame
    
    
    
    def __call__(self):

        cap = cv2.VideoCapture(self.capture_index)
        assert cap.isOpened()
        cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
        cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
      
        while True:
          
            start_time = time()
            
            ret, frame = cap.read()
            assert ret
            
            results = self.predict(frame)
            frame = self.plot_bboxes(results, frame)
            
            end_time = time()
            fps = 1/np.round(end_time - start_time, 2)
             
            cv2.putText(frame, f'FPS: {int(fps)}', (20,70), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0,255,0), 2)
            
            cv2.imshow('YOLOv8 Detection', frame)
 
            if cv2.waitKey(5) & 0xFF == 27:
                
                break
        
        cap.release()
        cv2.destroyAllWindows()
        
        
    
detector = ObjectDetection(capture_index=0)
detector()

The error outputted by the terminal.

Traceback (most recent call last):
  File "c:UsersusernameDownloadsVSC_YOLOV8_Applicationyolov8-silvayolov8_live.py", line 116, in <module>
    detector()
  File "c:UsersusernameDownloadsVSC_YOLOV8_Applicationyolov8-silvayolov8_live.py", line 97, in __call__
    frame = self.plot_bboxes(results, frame)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:UsersusernameDownloadsVSC_YOLOV8_Applicationyolov8-silvayolov8_live.py", line 72, in plot_bboxes
    self.labels = [f"{self.CLASS_NAMES_DICT[detection.class_id] if detection.class_id else None} {detection.confidence:0.2f}"
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "c:UsersusernameDownloadsVSC_YOLOV8_Applicationyolov8-silvayolov8_live.py", line 72, in <listcomp>
    self.labels = [f"{self.CLASS_NAMES_DICT[detection.class_id] if detection.class_id else None} {detection.confidence:0.2f}"
                                                                   ^^^^^^^^^^^^^^^^^^
AttributeError: 'tuple' object has no attribute 'class_id'

I tried looking on openstax/reddit for additional information. However, I was unable to find anything. Does anyone know how to resolve this?

Thank you!