opencv颜色处理与追踪_opencv.js 调色

一、opencv RGB颜色处理

图像是颜色的矩阵

1、拉流

import cv2 as cv
import numpy as np
 
cam = cv.VideoCapture(0)
cam.set(3,300)
 
#视频帧率
cam.set(5, 30)
cam.set(cv.CAP_PROP_BRIGHTNESS, 50) #设置亮度 -64 - 64  0.0
cam.set(cv.CAP_PROP_CONTRAST, 0)   #设置对比度 -64 - 64  2.0
cam.set(cv.CAP_PROP_EXPOSURE, 1000)  #设置曝光值 1.0 - 5000  156.0

2、读取与处理视频流

while True:
    # 读取视频流
    ret, frame = cam.read()
    #print(frame.shape)#查看图像大小
 
    #处理视频流
    b,g,r = cv.split(frame)
    #创建不同颜色的通道
    blue = cv.merge((b,blank,blank))
    green = cv.merge((blank,g,blank))
    red = cv.merge((blank,blank,r))
 
    # 显示视频流
    cv.imshow('Color-Channel', frame)
    cv.imshow('blue', blue)
    cv.imshow('green', green)
    cv.imshow('red', red)

3、关闭视频流

# ESC键退出
    keyCode = cv.waitKey(30) & 0xFF
    if keyCode == 27:
        break
 
cam.release()
cv.destroyAllWindows()

4、使用numpy创建空白图像

#用numpy绘制一个空白画面
blank = np.zeros([240,320,1],np.uint8)
cv.imshow('blank',blank)

5、显示效果

所有代码

# -*- coding: utf-8 -*-
import cv2 as cv
import numpy as np
 
cam = cv.VideoCapture(0)
cam.set(3,300)
 
#视频帧率
cam.set(5, 30)
cam.set(cv.CAP_PROP_BRIGHTNESS, 50) #设置亮度 -64 - 64  0.0
cam.set(cv.CAP_PROP_CONTRAST, 0)   #设置对比度 -64 - 64  2.0
cam.set(cv.CAP_PROP_EXPOSURE, 1000)  #设置曝光值 1.0 - 5000  156.0
 
#用numpy绘制一个空白画面
blank = np.zeros([240,320,1],np.uint8)
 
while True:
    # 读取视频流
    ret, frame = cam.read()
    #print(frame.shape)#查看图像大小
 
    #处理视频流
    b,g,r = cv.split(frame)
    #创建不同颜色的通道
    blue = cv.merge((b,blank,blank))
    green = cv.merge((blank,g,blank))
    red = cv.merge((blank,blank,r))
    merge=cv.merge((b,g,r))
 
    # 显示视频流
    cv.imshow('Color-Channel', frame)
    cv.imshow('blue', blue)
    cv.imshow('green', green)
    cv.imshow('red', red)
    cv.imshow('blank',blank)
    cv.imshow('merge',merge)
 
    # ESC键退出
    keyCode = cv.waitKey(30) & 0xFF
    if keyCode == 27:
        break
 
cam.release()
cv.destroyAllWindows()

二、RGB转成HSV筛选出要追踪的颜色

 HSV颜色模型

 

代码

# -*- coding: utf-8 -*-
import cv2 as cv
import numpy as np
 
def nothing(x):
    pass
 
cv.namedWindow('trackbars')
cv.resizeWindow('trackbars', 400,500)
cv.createTrackbar('huelower','trackbars',50,179,nothing)
cv.createTrackbar('huehigher','trackbars',100,179,nothing)
#追踪两种颜色
cv.createTrackbar('hue2lower','trackbars',50,179,nothing)
cv.createTrackbar('hue2higher','trackbars',100,179,nothing)
 
cv.createTrackbar('satlow','trackbars',100,255,nothing)
cv.createTrackbar('sathigh','trackbars',255,255,nothing)
cv.createTrackbar('vallow','trackbars',100,255,nothing)
cv.createTrackbar('valhigh','trackbars',255,255,nothing)
 
cam = cv.VideoCapture(0)
cam.set(3,300)
#用numpy绘制一个空白画面
blank = np.zeros([240,320,1],np.uint8)
 
while True:
    # 读取视频流
    ret, frame = cam.read()
    #print(frame.shape)#查看图像大小
    #处理视频流
    hsv = cv.cvtColor(frame,cv.COLOR_BGR2HSV)
    hl = cv.getTrackbarPos('huelower','trackbars')
    hu = cv.getTrackbarPos('huehigher','trackbars')
 
    hl2 = cv.getTrackbarPos('hue2lower', 'trackbars')
    hu2 = cv.getTrackbarPos('hue2higher', 'trackbars')
 
    sl = cv.getTrackbarPos('satlow','trackbars')
    sh = cv.getTrackbarPos('sathigh','trackbars')
    vl = cv.getTrackbarPos('vallow','trackbars')
    vh = cv.getTrackbarPos('valhigh','trackbars')
    # 选取颜色范围
    lower = np.array([hl, sl,vl])  # 转换为一维数组
    upper = np.array([hu, sh, vh])
 
    lower2 = np.array([hl2, sl,vl])  # 转换为一维数组
    upper2 = np.array([hu2, sh, vh])
 
 
    FGmask = cv.inRange(hsv,lower,upper)  # 设置HSV的阈值
    FGmask2 = cv.inRange(hsv,lower2,upper2)  # 设置HSV的阈值
    FGmaskComp=cv.add(FGmask, FGmask2)
    cv.imshow('FGmaskComp', FGmask)
    FG = cv.bitwise_and(frame,frame, mask=FGmaskComp)  # 将掩膜和图像逐像素相加
    cv.imshow('FG',FG)
    BGmask = cv.bitwise_not(FGmaskComp)
    cv.imshow('BGmask',BGmask)
    BG = cv.cvtColor(BGmask,cv.COLOR_GRAY2BGR)
    cv.imshow('BG', BG)
    final = cv.add(FG,BG)
    cv.imshow('final',final)
 
    # 显示视频流
    cv.imshow('Color-Channel', frame)
    # ESC键退出
    keyCode = cv.waitKey(30) & 0xFF
    if keyCode == 27:
        break
 
cam.release()
cv.destroyAllWindows()

 追踪2种颜色

常用颜色阈值

 三、根据物体颜色追踪物体

追踪效果

代码，可直接复制使用，根据上文常用颜色阈值调整要追踪的颜色

# -*- coding: utf-8 -*-
import cv2 as cv
import numpy as np
 
def nothing(x):
    pass
 
cv.namedWindow('trackbars')
cv.resizeWindow('trackbars', 400,500)
cv.createTrackbar('huelower','trackbars',50,179,nothing)
cv.createTrackbar('huehigher','trackbars',100,179,nothing)
#追踪两种颜色
cv.createTrackbar('hue2lower','trackbars',50,179,nothing)
cv.createTrackbar('hue2higher','trackbars',100,179,nothing)
 
cv.createTrackbar('satlow','trackbars',100,255,nothing)
cv.createTrackbar('sathigh','trackbars',255,255,nothing)
cv.createTrackbar('vallow','trackbars',100,255,nothing)
cv.createTrackbar('valhigh','trackbars',255,255,nothing)
 
cam = cv.VideoCapture(0)
cam.set(3,400)
#用numpy绘制一个空白画面
blank = np.zeros([480,640,1],np.uint8)
 
while True:
    # 读取视频流
    ret, frame = cam.read()
    #print(frame.shape)#查看图像大小
    #处理视频流
    hsv = cv.cvtColor(frame,cv.COLOR_BGR2HSV)
    hl = cv.getTrackbarPos('huelower','trackbars')
    hu = cv.getTrackbarPos('huehigher','trackbars')
    hl2 = cv.getTrackbarPos('hue2lower', 'trackbars')
    hu2 = cv.getTrackbarPos('hue2higher', 'trackbars')
    sl = cv.getTrackbarPos('satlow','trackbars')
    sh = cv.getTrackbarPos('sathigh','trackbars')
    vl = cv.getTrackbarPos('vallow','trackbars')
    vh = cv.getTrackbarPos('valhigh','trackbars')
    # 选取颜色范围
    lower = np.array([hl, sl,vl])  # 转换为一维数组
    upper = np.array([hu, sh, vh])
    lower2 = np.array([hl2, sl,vl])  # 转换为一维数组
    upper2 = np.array([hu2, sh, vh])
 
    FGmask = cv.inRange(hsv,lower,upper)  # 设置HSV的阈值
    FGmask2 = cv.inRange(hsv,lower2,upper2)  #设置HSV的阈值
    FGmaskComp=cv.add(FGmask, FGmask2)
    cv.imshow('FGmaskComp', FGmaskComp)
 
    #找到颜色外轮廓
    contours, hierarchy = cv.findContours(FGmaskComp, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
    contours = sorted(contours, key=lambda x: cv.contourArea(x), reverse=True)
    for cnt in contours:
        area = cv.contourArea(cnt)  # 计算轮廓面积
        (x,y,w,h)= cv.boundingRect(cnt)
        if area >= 50:
            #cv.drawContours(frame, [cnt], -1, (255, 0, 0),3)  # 画出图像轮廓
            cv.rectangle(frame,(x,y),(x+w,y+h),(255, 0, 0),3) #用矩形框画出轮廓
 
    # 显示视频流
    cv.imshow('nanocam', frame)
    # ESC键退出
    keyCode = cv.waitKey(30) & 0xFF
    if keyCode == 27:
        break
 
cam.release()
cv.destroyAllWindows()