机器视觉分拣python

# 机器视觉分拣python示例
# 1. 导入OpenCV库
import cv2
import numpy as np

# 2. 读取图像
image = cv2.imread('input_image.jpg')

# 3. 将图像转换为HSV颜色空间
hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

# 4. 定义颜色范围
lower_red = np.array([0, 100, 100])
upper_red = np.array([10,255, 255])

# 5. 根据颜色范围创建掩模
mask = cv2.inRange(hsv_image, lower_red, upper_red)

# 6. 寻找物体的轮廓
contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# 7. 遍历轮廓并计算质心
for contour in contours:
    M = cv2.moments(contour)
    if M["m00"] != 0:
        cX = int(M["m10"] / M["m00"])
        cY = int(M["m01"] / M["m00"])
        # 在图像上绘制质心
        cv2.circle(image, (cX, cY), 5, (255, 255, 255),-1)
        cv2.putText(image, "centroid", (cX - 25, cY - 25),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)

# 8. 显示结果图像
cv2.imshow("Result", image)
cv2.waitKey(0)
cv2.destroyAllWindows()