opencv 和 yolov8的代码

以下是 OpenCV 和 YOLOv3 的代码示例：

OpenCV：

import cv2

# 读取图片
img = cv2.imread('image.jpg')

# 转换为灰度图像
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 显示图像
cv2.imshow('image', img)
cv2.imshow('gray_image', gray_img)
cv2.waitKey(0)
cv2.destroyAllWindows()

YOLOv3：

import cv2
import numpy as np

# 加载 YOLOv3 模型
net = cv2.dnn.readNet("yolov3.weights", "yolov3.cfg")

# 加载类别标签
classes = []
with open("coco.names", "r") as f:
    classes = [line.strip() for line in f.readlines()]

# 读取图片
img = cv2.imread("image.jpg")

# 获取图像尺寸
height, width, _ = img.shape

# 将图像转换为 blob
blob = cv2.dnn.blobFromImage(img, 1 / 255.0, (416, 416), swapRB=True, crop=False)

# 设置输入层
net.setInput(blob)

# 获取输出层的名称
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]

# 进行前向传播
outs = net.forward(output_layers)

# 解析输出
class_ids = []
confidences = []
boxes = []
for out in outs:
    for detection in out:
        scores = detection[5:]
        class_id = np.argmax(scores)
        confidence = scores[class_id]
        if confidence > 0.5:
            center_x = int(detection[0] * width)
            center_y = int(detection[1] * height)
            w = int(detection[2] * width)
            h = int(detection[3] * height)
            x = center_x - w // 2
            y = center_y - h // 2
            class_ids.append(class_id)
            confidences.append(float(confidence))
            boxes.append([x, y, w, h])

# 进行非最大值抑制
indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)

# 绘制边框和标签
font = cv2.FONT_HERSHEY_PLAIN
colors = np.random.uniform(0, 255, size=(len(classes), 3))
for i in range(len(boxes)):
    if i in indexes:
        x, y, w, h = boxes[i]
        label = str(classes[class_ids[i]])
        color = colors[class_ids[i]]
        cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)
        cv2.putText(img, label, (x, y + 30), font, 3, color, 3)

# 显示图像
cv2.imshow("Image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

请注意，上述代码仅供参考，具体实现可能因不同的需求而有所不同。