OpenCV3.0+Python3.6实现特定颜色的物体追踪

一、环境

win10、Python3.6、OpenCV3.x；编译器：pycharm5.0.3

二、实现目标

根据需要追踪的物体颜色，设定阈值，在视频中框选出需要追踪的物体。

三、实现步骤

1）根据需要追踪的物体颜色，设定颜色阈值，获取追踪物体的掩膜

代码：generate_threshold.py

# -*- coding : utf-8 -*-
# Author: Tom Yu
import cv2
import numpy as np

cap = cv2.VideoCapture(0)#获取摄像头图像
# img = cv2.imread("timg1.jpg")
# hsv_img = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)

def nothing(x):
 pass
def createbars():
 """
 实现创建六个滑块的作用，分别控制H、S、V的最高值与最低值
 """
 cv2.createTrackbar("H_l","image",0,180,nothing)
 cv2.createTrackbar("H_h","image",0,180,nothing)
 cv2.createTrackbar("S_l","image",0,255,nothing)
 cv2.createTrackbar("S_h","image",0,255,nothing)
 cv2.createTrackbar("V_l","image",0,255,nothing)
 cv2.createTrackbar("V_h","image",0,255,nothing)
cv2.namedWindow("image")
createbars()#创建六个滑块

lower = np.array([0,0,0])#设置初始值
upper = np.array([0,0,0])
while True:
 ret,frame = cap.read()
 hsv_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)#将图片由BGR颜色空间转化成HSV空间，HSV可以更好地分割颜色图形
 lower[0]=cv2.getTrackbarPos("H_l","image")#获取"H_l"滑块的实时值
 upper[0]=cv2.getTrackbarPos("H_h","image")#获取"H_h"滑块的实时值
 lower[1]=cv2.getTrackbarPos("S_l","image")
 upper[1]=cv2.getTrackbarPos("S_h","image")
 lower[2]=cv2.getTrackbarPos("V_l","image")
 upper[2]=cv2.getTrackbarPos("V_h","image")

mask = cv2.inRange(hsv_frame,lower,upper)#cv2.inrange()函数通过设定的最低、最高阈值获得图像的掩膜
 cv2.imshow("img",frame)
 cv2.imshow("mask",mask)
 if cv2.waitKey(1)&0xff == 27:
   break

cv2.destroyAllWindows()

实现效果：获取需要追踪的物体颜色阈值

2）根据获取到的阈值，设定阈值范围，在视频中追踪特定颜色的物体并用框选框出所需追踪的物体

代码：tracking_object.py

# -*- coding : utf-8 -*-
# Author: Tom Yu
import cv2
import numpy as np

cap = cv2.VideoCapture(0)#获取摄像头视频

while True:
 ret,frame = cap.read()#读取每一帧图片
 hsv_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)#将每一帧图片转化HSV空间颜色
 """
 依据之前的脚本获取的阈值设置最高值与最低值
 """
 lower = np.array([0,104,205])
 upper = np.array([15,208,255])

mask = cv2.inRange(hsv_frame,lower,upper)
 img,conts,hier = cv2.findContours(mask,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)#找出边界
 cv2.drawContours(frame,conts,-1,(0,255,0),3)#画出边框
 dst = cv2.bitwise_and(frame,frame,mask=mask)#对每一帧进行位与操作，获取追踪图像的颜色
 #cv2.imshow("mask",mask)
 #cv2.imshow("dst",dst)
 cv2.imshow("frame",frame)
 if cv2.waitKey(1)&0xff == 27:
   break

cv2.destroyAllWindows()

实现效果：

来源：https://blog.csdn.net/qq_20156437/article/details/83026452