使用 YOLO 和 Webcam 实现实时目标检测

pip install opencv-python

import cv2
cap = cv2.VideoCapture(0)cap.set(3, 640)cap.set(4, 480)
while True:    ret, img= cap.read()    cv2.imshow('Webcam', img)
    if cv2.waitKey(1) == ord('q'):        break
cap.release()cv2.destroyAllWindows()

pip install ultralytics

from ultralytics import YOLOmodel = YOLO("yolo-Weights/yolov8n.pt")

classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",              "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",              "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",              "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",              "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",              "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",              "carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",              "diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",              "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",              "teddy bear", "hair drier", "toothbrush"              ]

import cv2
cap = cv2.VideoCapture(0)cap.set(3, 640)cap.set(4, 480)
while True:    ret, img= cap.read()    results = model(img, stream=True)
    cv2.imshow('Webcam', frame)
    if cv2.waitKey(1) == ord('q'):        break
cap.release()cv2.destroyAllWindows()

from ultralytics import YOLOimport cv2import math # start webcamcap = cv2.VideoCapture(0)cap.set(3, 640)cap.set(4, 480)
# modelmodel = YOLO("yolo-Weights/yolov8n.pt")
# object classesclassNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",              "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",              "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",              "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",              "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",              "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",              "carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",              "diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",              "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",              "teddy bear", "hair drier", "toothbrush"              ]

while True:    success, img = cap.read()    results = model(img, stream=True)
    # coordinates    for r in results:        boxes = r.boxes
        for box in boxes:            # bounding box            x1, y1, x2, y2 = box.xyxy[0]            x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) # convert to int values
            # put box in cam            cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
            # confidence            confidence = math.ceil((box.conf[0]*100))/100            print("Confidence --->",confidence)
            # class name            cls = int(box.cls[0])            print("Class name -->", classNames[cls])
            # object details            org = [x1, y1]            font = cv2.FONT_HERSHEY_SIMPLEX            fontScale = 1            color = (255, 0, 0)            thickness = 2
            cv2.putText(img, classNames[cls], org, font, fontScale, color, thickness)
    cv2.imshow('Webcam', img)    if cv2.waitKey(1) == ord('q'):        break
cap.release()cv2.destroyAllWindows()