文章目录有感于人工智能发展,现在开始学习Opencv关于计算机视觉的知识,又不想捣鼓C++代码,因此决定用Python来搞,此篇开始按照官网的教程开始学习,记录自己的学习历程,写一点笔记,方便以后查阅。 官方的教程:https://opencv-python-tutroals./en/latest/py_tutorials/py_tutorials.html GUI部分主要包括图像处理、视频处理、画图工具、GUI工具4个部分。 图像处理(Getting Started with Images)学习使用 读取图像
import cv2img = cv2.imread(r'/home/luke/图片/2018-08-09 11-58-52.jpg',cv2.IMREAD_COLOR)# filename参数u用于定位图片,可以是当前路径或绝对路径,注意windows平台,字符串前加 r# 第二项参数的默认值是:cv2.IMREAD_COLOR,读取色彩图像,还可以是# cv2.IMREAD_GRAYSCALE : 读取灰度图像# cv2.IMREAD_UNCHANGED : 读取图像包含 alpha channel
显示图像
cv2.imshow('image',img)#参数1:窗口标题名称#参数2:已读取的显示图像cv2.waitKey(0)# cv2.waitKey()函数等待任意按键, # 参数是等待超时时间,时间单位为ms;参数为0时,等待直到任意键按下,# 返回值是按下的键值cv2.destroyAllWindows()# 销毁所有打开的窗口123456789123456789 保存图像img = cv2.imread('/home/luke/图片/2018-07-19 19-47-33屏幕截图.png',0)cv2.imshow('image',img)k = cv2.waitKey(0)#k = cv2.waitKey(0) & 0xFFif k == 27: # wait for ESC key to exit cv2.destroyAllWindows()elif k == ord('s'): # wait for 's' key to save and exit cv2.imwrite('/home/luke/图片/test.png',img) cv2.destroyAllWindows()
使用Matplotlib使用Matplotlib库显示图像、缩放图像,保存图像,关于这个库的说明,需要另写文章。以下是简单示例 import numpy as npimport cv2from matplotlib import pyplot as pltimg = cv2.imread('messi5.jpg',0)plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')plt.xticks([]), plt.yticks([]) # to hide tick values on X and Y axisplt.show()# 注意:OpenCV图像存储格式为BGR模式,但是 Matplotlib 使用RGB模式;因此要想正确使用 Matplotlib库必须先进行转换。# convert BGR image to RGB image# cv2.cvtColor(img, cv2.COLOR_BGR2RGB)# img2 = img[:,:,::-1]123456789101112123456789101112 视频处理(Getting Started with Videos)主要学习函数:
读取摄像头播放视频要播放摄像头视频,需要先捕捉摄像头视频流,创造一个VideoCapture对象。 import numpy as npimport cv2cap = cv2.VideoCapture(0)#cap = cv2.VideoCapture(/dev/video0)#cap.read() returns a bool (True/False). If frame is read correctly, #it will be True. So you can check end of the video by checking this return valuewhile(True): # Capture frame-by-frame ret, frame = cap.read() # Our operations on the frame come here gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Display the resulting frame cv2.imshow('frame',gray) if cv2.waitKey(1) & 0xFF == ord('q'): break# When everything done, release the capturecap.release()cv2.destroyAllWindows()
播放视频文件import numpy as npimport cv2cap = cv2.VideoCapture('vtest.avi')while(cap.isOpened()): ret, frame = cap.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) cv2.imshow('frame',gray) if cv2.waitKey(1) & 0xFF == ord('q'): breakcap.release()cv2.destroyAllWindows()123456789101112123456789101112 注意: 保存视频文件以下代码一遍播放一遍保存视频文件 import numpy as npimport cv2cap = cv2.VideoCapture(0)# Define the codec and create VideoWriter objectfourcc = cv2.VideoWriter_fourcc(*'XVID')out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))while(cap.isOpened()): ret, frame = cap.read() if ret==True: frame = cv2.flip(frame,0) # write the flipped frame,垂直方向翻转 out.write(frame) cv2.imshow('frame',frame) if cv2.waitKey(1) & 0xFF == ord('q'): break else: break# Release everything if job is finishedcap.release()out.release()cv2.destroyAllWindows()
cv2.VideoWriter()参数说明:
OpenCV画图函数基本函数
基本参数
画线首先创建全黑图像,然后给出起点与终点坐标,线的颜色、厚度 import numpy as npimport cv2# Create a black imageimg = np.zeros((512,512,3), np.uint8)# Draw a diagonal blue line with thickness of 5 pximg = cv2.line(img,(0,0),(511,511),(255,0,0),5)1234567812345678 画矩形声明矩形的左上角坐标、右下角坐标 img = cv2.rectangle(img,(384,0),(510,128),(0,255,0),3)
画圆声明圆心点坐标、半径、颜色 img = cv2.circle(img,(447,63), 63, (0,0,255), -1)11 画椭圆椭圆参数:
img = cv2.ellipse(img,(256,256),(100,50),0,0,180,255,-1)
画多边形多边形参数:
pts = np.array([[10,5],[20,30],[70,20],[50,10]], np.int32)pts = pts.reshape((-1,1,2))img = cv2.polylines(img,[pts],True,(0,255,255))123123 注意:If third argument is False, you will get a polylines joining all the points, not a closed shape. 添加文字向图像添加文字需要声明以下参数
font = cv2.FONT_HERSHEY_SIMPLEXcv2.putText(img,'OpenCV',(10,500), font, 4,(255,255,255),2,cv2.LINE_AA)
以上步骤最终图像鼠标作为画图刷学习函数:cv2.setMouseCallback() 简单示例
import cv2import numpy as np# mouse callback functiondef draw_circle(event,x,y,flags,param): if event == cv2.EVENT_LBUTTONDBLCLK: cv2.circle(img,(x,y),100,(255,0,0),-1)# Create a black image, a window and bind the function to windowimg = np.zeros((512,512,3), np.uint8)cv2.namedWindow('image')cv2.setMouseCallback('image',draw_circle)while(1): cv2.imshow('image',img) if cv2.waitKey(20) & 0xFF == 27: breakcv2.destroyAllWindows()123456789101112131415161718123456789101112131415161718 高级示例鼠标回调函数绑定多个事件,既可以画圆也可以画矩形 import cv2import numpy as npdrawing = False # true if mouse is pressedmode = True # if True, draw rectangle. Press 'm' to toggle to curveix,iy = -1,-1# mouse callback functiondef draw_circle(event,x,y,flags,param): global ix,iy,drawing,mode if event == cv2.EVENT_LBUTTONDOWN: drawing = True ix,iy = x,y elif event == cv2.EVENT_MOUSEMOVE: if drawing == True: if mode == True: cv2.rectangle(img,(ix,iy),(x,y),(0,255,0),-1) else: cv2.circle(img,(x,y),5,(0,0,255),-1) elif event == cv2.EVENT_LBUTTONUP: drawing = False if mode == True: cv2.rectangle(img,(ix,iy),(x,y),(0,255,0),-1) else: cv2.circle(img,(x,y),5,(0,0,255),-1)
主循环检测“m”键,是否按下,用以切换画圆还是画矩形 img = np.zeros((512,512,3), np.uint8)cv2.namedWindow('image')cv2.setMouseCallback('image',draw_circle)while(1): cv2.imshow('image',img) k = cv2.waitKey(1) & 0xFF if k == ord('m'): mode = not mode elif k == 27: breakcv2.destroyAllWindows()1234567891011121312345678910111213 移动条调色板主要学习函数
import cv2import numpy as npdef nothing(x): pass# Create a black image, a windowimg = np.zeros((300,512,3), np.uint8)cv2.namedWindow('image')# create trackbars for color changecv2.createTrackbar('R','image',0,255,nothing)cv2.createTrackbar('G','image',0,255,nothing)cv2.createTrackbar('B','image',0,255,nothing)# create switch for ON/OFF functionalityswitch = '0 : OFF \n1 : ON'cv2.createTrackbar(switch, 'image',0,1,nothing)while(1): cv2.imshow('image',img) k = cv2.waitKey(1) & 0xFF if k == 27: break # get current positions of four trackbars r = cv2.getTrackbarPos('R','image') g = cv2.getTrackbarPos('G','image') b = cv2.getTrackbarPos('B','image') s = cv2.getTrackbarPos(switch,'image') if s == 0: img[:] = 0 else: img[:] = [b,g,r]cv2.destroyAllWindows()
好了,本片就这么多,继续学习! |
|