oculus cv2

1 Download OpenCV Source: http://opencv.org/releases.html recommended 2.4.13 version2 Installation dependencies:sudo apt-get install libgtk2.0-dev pkg-configsudo apt-get install build-essentialsudo apt-get install cmake3 Enter the unpacked folder and execute the cmake.4 Execute sudo make-j85 Execute sudo make install-j86 Copy the/usr/local/lib/python2.7/site-packages/cv2.so into the Python folder that you want to run. (or search

Environment: ubuntu16.04, Pycharm (using pyhon3.5 by default)Phenomenon: The use of Pycharm running program, Tip: No module named CV2, but the system has been installed PYTHON-OPENCV, no error at the terminal. proves that Pycharm did not import the relevant modules.Workaround: In the Pycharm project, under File/settins/project:similiar/project interpreter, add the required modules by searching.Right green + number addOpen the search interface and then

System support: Currently used by SDK0.4 support windows7,windows8,windows8.1,Mac(10.8, 10.9);Hardware configuration: The official standard configuration is 2.0+ghz above CPU,2GB memory, compatible with direct3d10 or OpenGL3 Graphics card (The

KNN is a simple algorithm used to classify data mining, which is used to realize the simple recognition of 4 flowers in this cluster.Environment: PYTHON2.7+OPENCV3.0+WINDOWS10Principle: After the use of KNN function to extract 4 flower feature points, the need to identify the image to extract the signs points, and the gallery of 4 flowers, compared to the category of the most matching points are considered similar.Code:Read in image data:1 2IMG =cv2.i

Xiao Qiang learns python+opencv -1.4.1 translation, rotation, scaling, flip-practice Xiao Qiang learns the Pythonopencv of 141 translation rotation and scaling flip summary of translation rotation Zoom summary Below, we translate, rotate, scale, and flip the theme pictures for this section.translation First, we create the Python script translation.py and add the following code: # import library Import NumPy as NP import argparse import cv2 # define

Part IVImage processing in the OpenCV16 Image SmoothingGoal? Learn to blur images using different low-pass filters? Convolution (2D convolution) of an image using a custom filterThe volume of the productAs with signals, we can also implement low-pass filtering (LPF), high-pass filtering (HPF), and so on for 2D images. LPF helps us to remove noise and blur images. HPF help us find the edge of the imageThe function cv.filter2d () provided by OpenCV allows us to perform convolution operations on an

has a special structure cv::mat, but Python has numpy this powerful basic tool, so the matrix is represented by NumPy array, Multi-channel is red-green-blue (RGB) three channels. 2.2 Basic Processing (1) Read image: Cv.imread () Can be read in different modes, usually the most commonly used to read a single channel grayscale, or directly read the default multi-channel (2) Storage Image: Cv.imwrite () Import cv2 color_img=

is successfulTest script:Import Cv2 #导入模块, OpenCV's Python module is called cv2imgobj = Cv2.imread (' pho.jpg ') #读取图像cv2. Namedwindow ("image") # Create the window and display the image type Cv2.imshow ("image", Imgobj) Cv2.waitkey (0) #等待事件触发, parameter 0 means t

Python-opencv extracts the contour of an image when there is noise, and python-opencv outlines For general image contour extraction, this blog introduces a good method, but for noisy images, the target object cannot be captured well. For example, for my mouse, the extracted contour is not good because of the noise: So this article adds the noise removal part. First load the original image and display the image 1 img = cv2.imread ("temp.jpg") # load t

Contours in the OpenCV1.1 What is a contourThe contours can be simply thought of as continuous points (connected to the boundary) linked together, with the same color or grayscale. Profiles are useful for shape analysis and object detection and recognition. For accuracy, use two to value the image. Threshold or canny boundary detection is required. Functions that look up outlines modify the original image. If you later want to continue using the original image, you should store the

Example of extracting the image contour with python-opencv under noisy conditions, python-opencv Contour A good method is introduced for extracting the outlines of general images. However, for noisy images, the target objects cannot be captured well. For example, for my mouse, the extracted contour is not good because of the noise: So this article adds the noise removal part. First load the original image and display the image Img = cv2.imread ("temp

The image threshold processing generally makes the image pixel value single, the image is simpler. Threshold can be divided into the global nature of the threshold, can also be divided into local properties of the threshold, can be a single threshold value can also be a multi-threshold value. Of course, the more thresholds are more complex. The three threshold methods under OpenCV are described below. (i) Simple threshold valueThe simple threshold is, of course, the simplest, choosing a glo

, lots of glass in the building", and you can search for the same area in other images. Basically, you are describing features. Similarly, the computer must describe the area around the feature so that it can find the same feature in other images. We refer to this description as a feature description. Once you have a description of the features, you can find the same feature in all the images and you can do whatever you want to do.In this chapter we are going to use the various algorithms in Ope

This record of several contrasting ways, mainly for mobile phone automation testing, by contrast to determine the correctness of the test, the way is as follows:#-*-coding:utf-8-*-"Use: Use Python to implement multiple methods to achieve image recognition Author:syw '" Import cv2 import numpy asNP fromMatplotlibImportPyplot asPLT # The simplest implementation of a grayscale histogram as a similar comparison def classify_gray_hist (Image1,image2,size=

For general image extraction outlines, this blog post describes a good method, but for noisy images, it is not very good to capture the target object.For example, for my mouse, the extracted contour effect is not good, because the noise is many:So this article adds the part that removes the noise.First load the original image and display the image1 img = cv2.imread ("temp.jpg") # load Image 2 h, w = Img.shape[:2]

Python OpenCV histogram calculation and display method example, pythonopencv This article introduces how to use OpenCV Python to calculate histograms, and briefly introduces how to use NumPy and Matplotlib to calculate and draw histograms. The background knowledge and usage of the histogram are omitted. Here we will introduce the method directly. Calculate and display the Histogram Like in C ++, The OpenCV histogram calculation function called in Python is c