|
|
import cv2
|
|
|
import numpy as np
|
|
|
|
|
|
|
|
|
# 视频源设置为电脑摄像头，0通常代表默认摄像头
|
|
|
cap = cv2.VideoCapture(0)
|
|
|
|
|
|
# 定义要追踪的颜色范围
|
|
|
# 注意：根据实际情况调整HSV值以精确匹配想要追踪的颜色
|
|
|
greenLower = np.array([(35, 46, 120)])
|
|
|
greenUpper = np.array([60, 255, 255])
|
|
|
|
|
|
while True:
|
|
|
# 从摄像头读取一帧
|
|
|
ret, frame = cap.read()
|
|
|
if not ret:
|
|
|
break
|
|
|
|
|
|
# 将BGR图像转换为HSV，因为HSV在颜色分割上更为直观
|
|
|
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
|
|
|
|
|
|
# 根据定义的HSV范围创建掩码
|
|
|
mask = cv2.inRange(hsv, greenLower, greenUpper)
|
|
|
|
|
|
# 对原图像和掩码应用位运算，提取出指定颜色部分
|
|
|
result = cv2.bitwise_and(frame, frame, mask=mask)
|
|
|
|
|
|
# 使用开运算和闭运算去除噪声
|
|
|
kernel = np.ones((5, 5), np.uint8)
|
|
|
mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
|
|
|
mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
|
|
|
|
|
|
# 查找轮廓
|
|
|
contours, _ = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
|
|
|
|
# 遍历轮廓，画出边界框
|
|
|
for contour in contours:
|
|
|
if cv2.contourArea(contour) > 100: # 过滤小面积噪点
|
|
|
x, y, w, h = cv2.boundingRect(contour)
|
|
|
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
|
|
|
|
|
|
# 显示原图、掩码和结果图像
|
|
|
cv2.imshow('Original', frame)
|
|
|
cv2.imshow('Mask', mask)
|
|
|
cv2.imshow('Result', result)
|
|
|
|
|
|
# 按'q'键退出循环
|
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
|
|
break
|
|
|
|
|
|
# 释放资源并关闭所有窗口
|
|
|
cap.release()
|
|
|
cv2.destroyAllWindows()
|
|
|
|
