目录
新的改变
做了功能上的强化,强化如下:
(1)加了pts清空,即当没有检测到目标时,清空pts,显示的图像上不再有轨迹;
(2)加了运动方向判别,能够判别目标的运动方向及当前坐标。
代码
# coding: utf-8
#!/usr/bin/env python
from collections import deque
import numpy as np
import time
#import imutils
import cv2
#设定红色阈值,HSV空间
redLower = np.array([170, 100, 100])
redUpper = np.array([179, 255, 255])
#初始化追踪点的列表
mybuffer = 16
pts = deque(maxlen=mybuffer)
counter = 0
#打开摄像头
camera = cv2.VideoCapture(0)
#等待两秒
time.sleep(3)
#遍历每一帧,检测红色瓶盖
while True:
#读取帧
(ret, frame) = camera.read()
#判断是否成功打开摄像头
if not ret:
print 'No Camera'
break
#frame = imutils.resize(frame, width=600)
#转到HSV空间
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
#根据阈值构建掩膜
mask = cv2.inRange(hsv, redLower, redUpper)
#腐蚀操作
mask = cv2.erode(mask, None, iterations=2)
#膨胀操作,其实先腐蚀再膨胀的效果是开运算,去除噪点
mask = cv2.dilate(mask, None, iterations=2)
cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
#初始化瓶盖圆形轮廓质心
center = None
#如果存在轮廓
if len(cnts) > 0:
#找到面积最大的轮廓
c = max(cnts, key = cv2.contourArea)
#确定面积最大的轮廓的外接圆
((x, y), radius) = cv2.minEnclosingCircle(c)
#计算轮廓的矩
M = cv2.moments(c)
#计算质心
center = (int(M["m10"]/M["m00"]), int(M["m01"]/M["m00"]))
#只有当半径大于10时,才执行画图
if radius > 10:
cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
cv2.circle(frame, center, 5, (0, 0, 255), -1)
#把质心添加到pts中,并且是添加到列表左侧
pts.appendleft(center)
else:#如果图像中没有检测到瓶盖,则清空pts,图像上不显示轨迹。
pts.clear()
for i in xrange(1, len(pts)):
if pts[i - 1] is None or pts[i] is None:
continue
#计算所画小线段的粗细
thickness = int(np.sqrt(mybuffer / float(i + 1)) * 2.5)
#画出小线段
cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
#判断移动方向
if counter >= 10 and i == 1 and len(pts) >= 10:
dX = pts[-10][0] - pts[i][0]
dY = pts[-10][1] - pts[i][1]
(dirX, dirY) = ("", "")
if np.abs(dX) > 20:
dirX = "East" if np.sign(dX) == 1 else "West"
if np.abs(dY) > 20:
dirY = "North" if np.sign(dY) == 1 else "South"
if dirX != "" and dirY != "":
direction = "{}-{}".format(dirY, dirX)
else:
direction = dirX if dirX != "" else dirY
cv2.putText(frame, direction, (20, 50), cv2.FONT_HERSHEY_SIMPLEX, 2,
(0, 255, 0), 3)
cv2.putText(frame, "dx: {}, dy: {}".format(dX, dY), (10, frame.shape[0] - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
cv2.imshow('Frame', frame)
#键盘检测,检测到esc键退出
k = cv2.waitKey(1)&0xFF
counter += 1
if k == 27:
break
#摄像头释放
camera.release()
#销毁所有窗口
cv2.destroyAllWindows()