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# 视频对象提取 # | ||
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与其说是视频对象提取,不如说是视频颜色提取,因为其本质还是使用了OpenCV的HSV颜色物体检测。 | ||
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# HSV介绍 # | ||
HSV分别代表,色调(H:hue),饱和度(S:saturation),亮度(V:value),由A. R. Smith在1978年创建的一种颜色空间, 也称六角锥体模型(Hexcone Model); | ||
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色调(H:hue):用角度度量,取值范围为0°~360°,从红色开始按逆时针方向计算,红色为0°,绿色为120°,蓝色为240°。它们的补色是:黄色为60°,青色为180°,品红为300°;(OpenCV中H的取值范围为0~180,8bit存储时); | ||
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饱和度(S:saturation):取值范围为0~255,值越大,颜色越饱和; | ||
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亮度(V:value):取值范围为0(黑色)~255(白色); | ||
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# 效果展示 # | ||
![](http://icdn.apigo.cn/hsv.gif) | ||
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# 实现思路 # | ||
如上效果图所示,我们要做的就是把视频中的绿色的小猪佩奇识别出来即可,下面是的识别步骤: | ||
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1. 使用PS取的小猪佩奇颜色的HSB值,相当于OpenCV的HSV,不过PS的HSV(HSB)取值是:0~360、0~1、0~1,而OpenCV的HSV是:0~180、0~255、0~255,所以要对ps的hsv进行处理,H/2、SV*255; | ||
1. 使用OpenCV位“与运算”提取HSV的颜色部分画面; | ||
2. 使用高斯模糊优化图片; | ||
3. 图片展示; | ||
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PS中工具栏右侧HSB显示: | ||
![](http://icdn.apigo.cn/hsb.png) | ||
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# 完整代码 # | ||
``` | ||
#coding=utf-8 | ||
#HSV转换(颜色提取) | ||
import cv2 | ||
import numpy as np | ||
cap = cv2.VideoCapture(0) | ||
while (1): | ||
_, frame = cap.read() | ||
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) | ||
#在PS里用取色器的HSV | ||
psHSV = [112, 89, 52] | ||
diff = 40 #上下浮动值 | ||
#因为PS的HSV(HSB)取值是:0~360、0~1、0~1,而OpenCV的HSV是:0~180、0~255、0~255,所以要对ps的hsv进行处理,H/2、SV*255 | ||
lowerHSV = [(psHSV[0] - diff) / 2, (psHSV[1] - diff) * 255 / 100, | ||
(psHSV[2] - diff) * 255 / 100] | ||
upperHSV = [(psHSV[0] + diff) / 2, (psHSV[1] + diff) * 255 / 100, | ||
(psHSV[2] + diff) * 255 / 100] | ||
mask = cv2.inRange(hsv, np.array(lowerHSV), np.array(upperHSV)) | ||
#使用位“与运算”提取颜色部分 | ||
res = cv2.bitwise_and(frame, frame, mask=mask) | ||
#使用高斯模式优化图片 | ||
res = cv2.GaussianBlur(res, (5, 5), 1) | ||
cv2.imshow('frame', frame) | ||
# cv2.imshow('mask', mask) | ||
cv2.imshow('res', res) | ||
if cv2.waitKey(1) & 0xFF == ord('q'): | ||
break | ||
cv2.destroyAllWindows() | ||
``` | ||
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