--- category: tool tool: OpenCV filename: learnopencv.py contributors: - ["Yogesh Ojha", "http://github.com/yogeshojha"] translators: - ["GengchenXU", "https://github.com/GengchenXU"] lang: zh-cn --- ### Opencv 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 #### 安装 有关在计算机上安装 OpenCV，请参阅这些文章。 * 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]() * Mac 安装说明 (High Sierra): [https://medium.com/@nuwanprabhath/installing-opencv-in-macos-high-sierra-for-python-3-89c79f0a246a]() * Linux 安装说明 （Ubuntu 18.04): [https://www.pyimagesearch.com/2018/05/28/ubuntu-18-04-how-to-install-opencv]() ### 在这里，我们将专注于 OpenCV 的 python 实现 ```python # OpenCV读取图片 import cv2 img = cv2.imread('cat.jpg') # 显示图片 # imshow() 函数被用来显示图片 cv2.imshow('Image',img) # 第一个参数是窗口的标题，第二个参数是image # 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 cv2.waitKey(0) # 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。 # Writing an image cv2.imwrite('catgray.png',img) # 第一个参数是文件名，第二个参数是图像 # 转换图像灰度 gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 从摄像头捕捉视频 cap = cv2.VideoCapture(0) #0 是你的相机，如果你有多台相机，你需要输入他们的id while(True): # 一帧一帧地获取 _, frame = cap.read() cv2.imshow('Frame',frame) # 当用户按下q ->退出 if cv2.waitKey(1) & 0xFF == ord('q'): break # 相机必须释放 cap.release() # 在文件中播放视频 cap = cv2.VideoCapture('movie.mp4') while(cap.isOpened()): _, frame = cap.read() # 灰度播放视频 gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.imshow('frame',gray) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() # 在OpenCV中画线 # 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) cv2.line(img,(0,0),(511,511),(255,0,0),5) # 画矩形 # cv2.rectangle(img,(x,y),(x1,y1),(color->r,g,b->0 to 255),thickness) # 粗细= -1用于填充矩形 cv2.rectangle(img,(384,0),(510,128),(0,255,0),3) # 画圆 cv2.circle(img,(xCenter,yCenter), radius, (color->r,g,b->0 to 255), thickness) cv2.circle(img,(200,90), 100, (0,0,255), -1) # 画椭圆 cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1) # 在图像上增加文字 cv2.putText(img,"Hello World!!!", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 2, 255) # 合成图像 img1 = cv2.imread('cat.png') img2 = cv2.imread('openCV.jpg') dst = cv2.addWeighted(img1,0.5,img2,0.5,0) # 阈值图像 # 二进制阈值 _,thresImg = cv2.threshold(img,127,255,cv2.THRESH_BINARY) # Adaptive Thresholding adapThres = cv2.adaptiveThreshold(img,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2) # 模糊的形象 # 高斯模糊 blur = cv2.GaussianBlur(img,(5,5),0) # 模糊中值 medianBlur = cv2.medianBlur(img,5) # Canny 边缘检测 img = cv2.imread('cat.jpg',0) edges = cv2.Canny(img,100,200) # 用Haar Cascades进行人脸检测 # 下载 Haar Cascades 在 https://github.com/opencv/opencv/blob/master/data/haarcascades/ import cv2 import numpy as np face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') img = cv2.imread('human.jpg') gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) aces = face_cascade.detectMultiScale(gray, 1.3, 5) for (x,y,w,h) in faces: cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) roi_gray = gray[y:y+h, x:x+w] roi_color = img[y:y+h, x:x+w] eyes = eye_cascade.detectMultiScale(roi_gray) for (ex,ey,ew,eh) in eyes: cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2) cv2.imshow('img',img) cv2.waitKey(0) cv2.destroyAllWindows() # destroyAllWindows() destroys all windows. # 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。 ``` ### 进一步阅读： * Download Cascade from [https://github.com/opencv/opencv/blob/master/data/haarcascades]() * OpenCV 绘图函数 [https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html]() * 最新的语言参考 [https://opencv.org]() * 更多的资源 [https://en.wikipedia.org/wiki/OpenCV]() * 优秀的的 OpenCV 教程 * [https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_tutorials.html]() * [https://realpython.com/python-opencv-color-spaces]() * [https://pyimagesearch.com]() * [https://www.learnopencv.com]()