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HSV_color.py
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96 lines (75 loc) · 2.72 KB
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# -*- coding: cp936 -*-
#中文，你懂得
'''
此脚本是用来检测物体的HSV光学属性，如颜色亮度等信息
#此脚本是windows环境python 2.7+opencv3.2版本的， 配置见下面的链接
https://github.com/wjb711/Opencv_learning/blob/master/windows_python2.7_opencv3.2%E5%AE%89%E8%A3%85%E9%85%8D%E7%BD%AE%E6%8C%87%E5%AF%BC.txt
#需要提前安装speech模块， 安装方法pip install speech
其中，阀值1和2代表H色彩， 3和4代表S纯度，5和6代表V明度
关于HSV的介绍，请看这里
http://blog.csdn.net/jianjian1992/article/details/51274834
点击屏幕屏幕上的点， 可以看到对应的X,Y的值，RGB的值以及HSV的值
'''
import cv2
import numpy as np
import sys
def nothing(x):
pass
def draw_circle(event,x,y,flags,param):
#if event == cv2.EVENT_LBUTTONDBLCLK:
if event == cv2.EVENT_LBUTTONDOWN:
print ('mouse x and y is ')
print (x,y)
px = frame[y,x]
print ('RGB Value:')
print px
px_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
H=px_hsv.item(y,x,0)
S=px_hsv.item(y,x,1)
V=px_hsv.item(y,x,2)
print ('HSV Value: H是颜色，S是纯度，V是亮度')
print (H,S,V)
cap = cv2.VideoCapture(0)
try:
ret = cap.set(3,1280)
ret = cap.set(3,960)
except:
ret = cap.set(3,640)
ret = cap.set(3,480)
#尝试用1280x960打开摄像头， 如果失败， 使用默认的640x480
print ('实际分辨率为')
print cap.get(3)
print cap.get(4)
cv2.namedWindow('颜色捕捉',0)
cv2.createTrackbar('色彩最低', '颜色捕捉', 0, 180, nothing)
cv2.createTrackbar('色彩最高', '颜色捕捉', 255, 255, nothing)
cv2.createTrackbar('纯度最低', '颜色捕捉', 0, 255, nothing)
cv2.createTrackbar('纯度最高', '颜色捕捉', 255, 255, nothing)
cv2.createTrackbar('亮度最低', '颜色捕捉', 0, 255, nothing)
cv2.createTrackbar('亮度最高', '颜色捕捉', 255, 255, nothing)
cv2.setMouseCallback('颜色捕捉',draw_circle)
while(1):
# Take each frame
_, frame = cap.read()
# Convert BGR to HSV
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
thrs1 = cv2.getTrackbarPos('色彩最低', '颜色捕捉')
thrs2 = cv2.getTrackbarPos('色彩最高', '颜色捕捉')
thrs3 = cv2.getTrackbarPos('纯度最低', '颜色捕捉')
thrs4 = cv2.getTrackbarPos('纯度最高', '颜色捕捉')
thrs5 = cv2.getTrackbarPos('亮度最低', '颜色捕捉')
thrs6 = cv2.getTrackbarPos('亮度最高', '颜色捕捉')
# define range of blue color in HSV
lower_blue = np.array([thrs1,thrs3,thrs5])
upper_blue = np.array([thrs2,thrs4,thrs6])
# Threshold the HSV image to get only blue colors
mask = cv2.inRange(hsv, lower_blue, upper_blue)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame,frame, mask= mask)
#cv2.imshow('frame',frame)
#cv2.imshow('mask',mask)
cv2.imshow('颜色捕捉',res)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
cv2.destroyAllWindows()