If you love working on image processing and video analysis using python then you have come to the right place. Python is one of the major languages that can be used to process images or videos.
Requirements for OpenCV and Anaconda
– 32- or a 64-bit computer.
– For Miniconda—400 MB disk space.
– For Anaconda—Minimum 3 GB disk space to download and install.
– Windows, macOS or Linux.
– Python 2.7, 3.4, 3.5 or 3.6.
Anaconda is a open source software that contains jupiter, spyder etc that are used for large data processing, data analytics, heavy scientific computing. Anaconda works for R and python programming language. Spyder(sub-application of Anaconda) is used for python.Opencv for python will work in skyder. Package versions are managed by the package management system conda.
Installing Anaconda : Head over to continuum.io/downloads/ and install the latest version of Anaconda. Make sure to install the “Python 3.6 Version” for the appropriate architecture. Install it with the default settings.
OpenCV (Open Source Computer Vision) is a computer vision library that contains various functions to perform operations on pictures or videos. It was originally developed by Intel but was later maintained by Willow Garage and is now maintained by Itseez. This library is cross-platform that is it is available on multiple programming language such as Python, C++ etc.
Steps to import opencv on anaconda in windows environment‘
- Creating Anaconda Environment :
Step 1:- Search Anaconda in your task bar and select ANACONDA NAVIGATOR.
Step 2:- Now you will see a menu with various options like Jupiter notebook , Spyder etc. This is Anaconda Environment.
Step 3:- Select Spyder as it is Anaconda’s IDE for python and OpenCV library will work in it only.
- Install OpenCV
Step 1 :- After installing the anaconda open the Anaconda Prompt.
conda install -c menpo opencv
Step 3 :- Now simply import opencv in your python program in which you want to use image processing functions.
Examples: Some basic functions of the opencv library (These functions are performed on Windows flavour of Anaconda but it will work on linux flavor too)
- Reading a image
img = cv2.imread('LOCATION OF THE IMAGE')
The above function imread stores the image at the given location to the variable img.
- Converting a image to greyscale
img = cv2.imread('watch.jpg',cv2.IMREAD_GRAYSCALE)
The above function converts the image to grayscale and then stores it in the variable img.
- Showing the stored image
The above function shows the image stored in img variable.
- Save an image to a file
The above function stores the image to the file. The image is stored in the variable of type Mat that is in the form of a matrix.
- Reading video directly from the webcam
cap = cv2.VideoCapture(0)
Stores live video from your webcam in variable cap.
- Reading a video from local storage
cap = cv2.VideoCapture('LOCATION OF THE VIDEO')
Stores the video located in the given location to the variable.
- To check if the video is successfully stored in the variable
cap is the variable that contains the video. The above function returns true if the video is successfully opened else returns false.
- Release the stored video after processing is done
The above function releases the video stored in cap.
- Python | Add packages to Anaconda environment
- C++, OpenCV and Gtk3 Windows dev environment
- Python Virtual Environment | Introduction
- How Can Machine Learning Save the Environment From Disaster?
- Create virtual environment using venv | Python
- Creating Python Virtual Environment in Windows and Linux
- Introduction to OpenCV
- Image Inpainting using OpenCV
- Histograms Equalization in OpenCV
- Python OpenCV | cv2.putText() method
- Python OpenCV | cv2.ellipse() method
- Python OpenCV | cv2.blur() method
- Color Spaces in OpenCV | Python
- Python | Smile detection using OpenCV
- Image Processing without OpenCV | Python
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.
Improved By : aligbashi