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zh-cn/opencv-cn.html.markdown
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zh-cn/opencv-cn.html.markdown
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---
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category: tool
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tool: OpenCV
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filename: learnopencv.py
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contributors:
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- ["Yogesh Ojha", "http://github.com/yogeshojha"]
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translators:
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- ["GengchenXU", "https://github.com/GengchenXU"]
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lang: zh-cn
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---
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### Opencv
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Opencv(开源计算机视觉)是一个编程功能库,主要面向实时计算机视觉。最初由英特尔开发,后来由Willow Garage,然后Itseez(后来被英特尔收购)支持。Opencv 目前支持多种语言,如C++、Python、Java 等
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#### 安装
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有关在计算机上安装 OpenCV,请参阅这些文章。
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* Windows 安装说明: [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_setup/py_setup_in_windows/py_setup_in_windows.html#install-opencv-python-in-windows]()
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* Mac 安装说明 (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a]()
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* Linux 安装说明 (Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv]()
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### 在这里,我们将专注于 OpenCV 的 python 实现
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```python
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# OpenCV读取图片
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import cv2
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img = cv2.imread('cat.jpg')
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# 显示图片
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# imshow() 函数被用来显示图片
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cv2.imshow('Image',img)
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# 第一个参数是窗口的标题,第二个参数是image
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# 如果你得到错误,对象类型为None,你的图像路径可能是错误的。请重新检查图像包
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cv2.waitKey(0)
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# waitKey() 是一个键盘绑定函数,参数以毫秒为单位。对于GUI事件,必须使用waitKey()函数。
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# Writing an image
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cv2.imwrite('catgray.png',img)
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# 第一个参数是文件名,第二个参数是图像
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# 转换图像灰度
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gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 从摄像头捕捉视频
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cap = cv2.VideoCapture(0)
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#0 是你的相机,如果你有多台相机,你需要输入他们的id
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while(True):
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# 一帧一帧地获取
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_, frame = cap.read()
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cv2.imshow('Frame',frame)
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# 当用户按下q ->退出
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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# 相机必须释放
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cap.release()
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# 在文件中播放视频
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cap = cv2.VideoCapture('movie.mp4')
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while(cap.isOpened()):
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_, frame = cap.read()
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# 灰度播放视频
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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cv2.imshow('frame',gray)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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cap.release()
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# 在OpenCV中画线
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# cv2.line(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)(注 color颜色rgb参数 thickness粗细)
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cv2.line(img,(0,0),(511,511),(255,0,0),5)
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# 画矩形
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# cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness)
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# 粗细= -1用于填充矩形
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cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
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# 画圆
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cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness)
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cv2.circle(img,(200,90), 100, (0,0,255), -1)
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# 画椭圆
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cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
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# 在图像上增加文字
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cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255)
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# 合成图像
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img1 = cv2.imread('cat.png')
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img2 = cv2.imread('openCV.jpg')
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dst = cv2.addWeighted(img1,0.5,img2,0.5,0)
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# 阈值图像
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# 二进制阈值
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_,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY)
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# Adaptive Thresholding
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adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
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# 模糊的形象
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# 高斯模糊
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blur = cv2.GaussianBlur(img,(5,5),0)
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# 模糊中值
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medianBlur = cv2.medianBlur(img,5)
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# Canny 边缘检测
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img = cv2.imread('cat.jpg',0)
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edges = cv2.Canny(img,100,200)
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# 用Haar Cascades进行人脸检测
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# 下载 Haar Cascades 在 https://github.com/opencv/opencv/blob/master/data/haarcascades/
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import cv2
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import numpy as np
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face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
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eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
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img = cv2.imread('human.jpg')
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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aces = face_cascade.detectMultiScale(gray, 1.3, 5)
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for (x,y,w,h) in faces:
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cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
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roi_gray = gray[y:y+h, x:x+w]
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roi_color = img[y:y+h, x:x+w]
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eyes = eye_cascade.detectMultiScale(roi_gray)
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for (ex,ey,ew,eh) in eyes:
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cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
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cv2.imshow('img',img)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# destroyAllWindows() destroys all windows.
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# 如果您希望销毁特定窗口,请传递您创建的窗口的确切名称。
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```
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### 进一步阅读:
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* Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades]()
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* OpenCV 绘图函数 [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html]()
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* 最新的语言参考 [https://opencv.org]()
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* 更多的资源 [https://en.wikipedia.org/wiki/OpenCV]()
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* 优秀的的 OpenCV 教程
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* [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html]()
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* [https://realpython.com/python-opencv-color-spaces]()
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* [https://pyimagesearch.com]()
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* [https://www.learnopencv.com]()
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