opencv python tutorial

specified window6. Save the imageCv2.imwrite (Save_path, Image,[int (mode), Num])Save the function, a total of three parameters, the first to save the file path, the second is read in the picture. The third parameter is optional for Jpeg,[int (CV2. imwrite_jpeg_quality), 5], which represents the quality of the image, represented by a 0-100 integer, the default is 95; For PNG, the third parameter represents the compression level. Cv2. Imwrite_png_compression, from 0 to 9, the higher the compress

Chapter Three: The basic operation of the imageOne, the knowledge point1. Frame: Video is composed of a picture, each image is called a frame2. Frame rate: The number of frames per second (one image), Unit fps (frames per second)3. OpenCV the color channel sequence inside the image is bgr,matplotlib in the order is RGBSecond, the function involvedA. Picture1. Cv2.imread (filename, flags)FileName: Picture file name, note the path problemFlags: Optional

Content from Opencv-python tutorials own translation finishing Target:Use the scroll bar to bind a windowLearn the following functions Cv2.gettrackbarpos (), Cv2.createtrackbar () Sample code:Here is a simple example to create a realistic user-specified color. The user uses three scroll bars to specify the B,g,r value, and the user-selected color is displayed in the window. The user drags the scroll bar to

The following features are implemented with Opencv+python:1) Get real-time video, decompose frame frequency;2) The video to do two value processing;3) The Video filter processing (to remove noise, to obtain the exact number of profiles);4) identify image contour;5) Calculate the centroid;6) depict the dynamic change curve of centroid;#-*-Coding:utf-8-*-"" "Created on Thu Apr 12:10:23 2018@author:irene" "" I

Content from Opencv-python tutorials own translation finishing Target:Gets the pixel value and modifiesGet Image PropertiesSet Image AreaSegmenting and stitching Images The above content is important to the NumPy library operation in Python, and it is important to use the NumPy library skillfully gets the pixel value and modifiesThe image value can be obtained by

effects.fontscale– font size, this value is multiplied by the font built-in size to get the font sizecolor– text colorthickness– the thickness of the line, similar to the 0.38 nib and the 0.5 niblinetype– linear.Bottomleftorigin–true, the image data origin is in the lower left corner. Otherwise, the image data origin is in the upper left corner.Case codeImportNumPy asNpImportCv2img=Np.zeros (( +, +,3), np.uint8) Cv2.line (IMG, (0,0),(511,511),(255,0,0),5) Cv2.rectangle (IMG, (384,0),(510, -),(0

Content from Opencv-python tutorials own translation finishing TargetBlur the image using different Low-pass filtersFilter the image using a custom filter (two-dimensional convolution) 2D convolution (image filtering)The image can be low pass filter and High-pass filter, Low-pass filter can make the image remove noise, high pass filter can find the edge of the image.OPENCV provides a cv2.filter2d function f

Some information: http://blog.csdn.net/sunny2038/article/details/9057415 a very good blog Http://docs.opencv.org/trunk/doc/py_tutorials official Python's tutorial OpenCV for Python's skeleton project is not supported by some operators such as sift Backbone Project Address: HTTPS://GITHUB.COM/ITSEEZ/OPENCVExtension Project address: Https://github.com/Itseez/opencv_contribThe backbone project is

1, installation package download: Download the corresponding version and platform on the following URL. WHL package, and then manually install.https://www.lfd.uci.edu/~gohlke/pythonlibs/2. Copy it to the \lib\site-packages folder under the Python directory, open the command line (shift+ right) in this directory, or CD into this directory, enter:Pip Install Opencv_python? 3.3. 1. CP36?CP36M?WIN_AMD64.WHLThe installation is complete and ready to use imp

error of the model depends on the training data, the perfect form of the model is a defective model based on the perfect database. At the same time, it is more intuitive to see the shape of the skin color in the RGB colour space than to test the complexion with a picture. I found it. Experimental results of the training data set: The color space is determined by the possibility of 90%,80%,70% and 60% in order from left to right, from top to bottom.Conclusion this part of the experimental result

In the work of image processing, scripting language is used more, in recent years, with the development of Python, script programming becomes more easily accessible. With Open Source Library OpenCV, Python can be used to do some image processing work, here are two simple examples of actual image processing. Header files to be introduced: Import cv2 import numpy

What to do without a USB camera. It's okay to have an Android phone, we can turn it into a webcam. 1. Install a mobile phone called [IP Camera] app, get IP address, account password 2. Install Python and OpenCV 3. Execute the Python script below, and notice that you want to change the IP address to the one displayed on your phone. #coding =utf-8 Import CV2.CV as

Python + opencv for Dynamic Object Recognition, pythonopencv Note: This method is very affected by light changes. Figure of the result of your mobile phone shaking at home: Source code: #-*-Coding: UTF-8-*-"Created on Wed Sep 27 15:47:54 2017 @ author: tina" import cv2 import numpy as np camera = cv2.VideoCapture (0) # parameter 0 indicates the first camera # determine whether the video is enabled if (came

Here's a small piece to bring you an example of Python using OpenCV to read pictures. Small series feel very good, now share to everyone, also for everyone to make a reference. Let's take a look at it with a little knitting. After installing the environment, start the first Hello Word example, how to read the picture, save the artwork Import CV2 Import NumPy as NP import Matplotlib.pyplot as PLT #读取图片代码

Detection code is as follows:#encoding: Utf-8##Sobel边缘检测#Import NumPy as Npimport cv2image = Cv2. Imread("H:\\img\\lena.jpg") image = Cv2. Cvtcolor(Image,cv2. COLOR_bgr2gray)#将图像转化为灰度图像Cv2. Imshow("Original", image) Cv2. Waitkey()#Sobel边缘检测Sobelx = Cv2. Sobel(Image,cv2. CV_64f,1,0)#x方向的梯度sobely = Cv2. Sobel(Image,cv2. CV_64f,0,1)#y方向的梯度SOBELX = NP. UINT8 (NP. Absolute(SOBELX))#x方向梯度的绝对值sobely = NP. UINT8 (NP. Absolute(sobely))#y方向梯度的绝对值sobelcombined = Cv2. Bitwise_or (sobelx,sobely)#Cv2. Imshow

. Original image2. HSV Space5. RGB Turn LabThe code is as follows:#encoding:utf-8import numpy as npimport cv2image = cv2.imread("H:\\img\\lena.jpg")cv2.imshow("Original",image)cv2.waitKey(0)#lab空间lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)cv2.imshow("L*a*b*", lab)cv2.waitKey(0)The results are as follows1. Original image2. Lab Space Copyright NOTICE: This article for Bo Master original article, without Bo Master permission not reproduced. Opencv-

Some indexes and modify the image pixel point data and other operations, can print the observation of the running results.#-*-Coding:utf-8-*-"" "Created on Wed Sep-00:11:07 2016@author:administrator" "" Import cv2import NumPy as np# length , 588;width,468img = Cv2.imread (' cute.jpg ') px = Img[100,100]print (px) # Accessing only blue pixel# remember b,g,rblue = img[ 100,100,0]print (blue) # Modify the pixelimg[100,100] = [255,255,255]# accesing RED valuep_item = Img.item (10,10,2) # Modyfy ing

first, the function is simple introduction1, imread-read the image function prototype: imread (filename, flags=none) FileName: Read the image path name, for example: "H:\img\lena.jpg". Flags: Color graph or gray figure, 1: Color graph. 0: Gray figure. 2. imshow-Display image function prototype: Imshow (Winname, Mat) winname: Form name. For example: "Lena". Mat: The image matrix to display. 3, imwrite-save image Function prototype: imwrite (FileName, img, params=none) FileName: The name of the im

, I actually read the online code, such as http://blog.csdn.net/szfhy/article/details/51087301The picture after my frame is like thisThe heart is broken, the baby just want a rectangular box ~Originally I want to draw a rectangle box, there is a rectangle box with the mouse drag size changes, and only a rectangular box, the mouse lifted, the rectangle is determined. Temporarily do not know how to achieve, have to know can exchange, hehe ~PYTHON+

(W): + forJinchRange (h): - ifBINARY[I,J] = =0: thetemp ="0" * elifBINARY[I,J] = = 255: $temp ="1"Panax Notoginseng f.write (temp) -F.write ("\ r \ n") the f.close () + #print (Temp.shape) A defMain (): theimg = Cv.imread ("1.JPG") + #Cv.namedwindow ("Show", CV. Window_autosize) -Cv.imshow ("Show", IMG) $t = Jinzita (3, IMG) $binary=local_threshold (t) - result (binary) - cv.waitkey (0) the cv.destroyallwindows () - WuyiMain ()18,