Opencv识别图片颜色并绘制轮廓实现代码示例

import cv2
import numpy as np

# 1. 输入图片并调整大小
img = cv2.imread("./color_1.png")
if img is None:
    print("无法加载图片，请检查路径！")
    exit()
img = cv2.resize(img, (0, 0), fx=0.7, fy=0.7)

# 2. 转换 HSV 颜色空间
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

# 3. 定义颜色范围并生成二值掩膜
yellow_min = np.array([26, 43, 46])  # 黄色下界
yellow_max = np.array([34, 255, 255])  # 黄色上界
img_mask = cv2.inRange(img_hsv, yellow_min, yellow_max)

# 4. 中值滤波去噪
img_blur = cv2.medianBlur(img_mask, 7)

# 5. 形态学变换 - 开运算
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
img_open = cv2.morphologyEx(img_blur, cv2.MORPH_OPEN, kernel)

# 6. 轮廓提取
contours, _ = cv2.findContours(img_open, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# 7. 遍历轮廓并绘制
img_result = img.copy()
for contour in contours:
    area = cv2.contourArea(contour)
    if area < 200 or area > 200000:  # 根据面积过滤无效轮廓
        continue
    cv2.drawContours(img_result, [contour], -1, (0, 0, 255), 2)  # 绘制轮廓

# 8. 显示结果
cv2.imshow("Original Image", img)
cv2.imshow("Filtered Contours", img_result)

cv2.waitKey(0)
cv2.destroyAllWindows()