Skip to main content

Installation of OpenCV2 / OpenCV3 with Python and Anaconda

This is first tutorial of the series beginning with installation instruction of opencv2 / opencv3 in python anaconda virtual Environment . We will come with lot of exciting blog like face detection and recognition in video/image/livestream , object or people tracking etc , So stay tuned and subscribe for more updates .

We are installing it on MAC OS , you need below tools to setup OpenCV:
  1. Xcode
  2. Homebrew
  3. Anaconda
  4. OS X

Step 1: Install Xcode

  1. Go to App Store , Search for Xcode
  2. Install it .

Step 2: Install HomeBrew
  1. Open Terminal(Application->Utilites->terminal)
  2. Write this following in terminal:
ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
brew install python

Step 3: Install Anaconda Python Package

Follow the Installation instructions, should be pretty standard, however Continuum has a guide here.
Type Conda Info and check Installation . click here for Anaconda cheat sheet .

Step 4: Create Conda Virtual Env and setup OpenCV

You can choose either OpenCV2 OR openCV3 

OpenCV2 Installation
Execute below commands in your terminal
conda create --name ComputerVision python=2.7 -y
Conda activate ComputerVision
conda install -c menpo opencv -y
pip install opencv-python
conda install -c anaconda numpy -y
conda install pandas -y
conda install -c anaconda sqlalchemy -y
conda install -c conda-forge matplotlib -y
OpenCV3 Installation
Execute below commands in your terminal
conda create --name ComputerVision3.5 python=3.5
Conda activate ComputerVision3.5
conda install -c menpo opencv3
pip3 install opencv-python
conda install -c anaconda numpy
conda install pandas
conda install -c anaconda sqlalchemy
conda install -c conda-forge matplotlib

Step 5: Execute code in Jupyter Notebook

  1. Open Terminal
  2. Activate Conda environment using : Conda activate ComputerVision3.5
  3. Type ipython OR jupyter notebook in terminal
  4. Open New Notebook if jupyter notebook chosen .
  5. Type Below commands to check installation :
    1. import cv2
    2. import numpy as np
    3. Print('Importing Libraries')



If you still facing any issues . Leave a comment here OR go to my youtube video :





















    Labels:

    Comments

    Post a Comment

    Popular posts from this blog

    Long-Polling vs WebSockets vs Server-Sent Events

    Long-Polling vs WebSockets vs Server-Sent Events  Long-Polling, WebSockets, and Server-Sent Events are popular communication protocols between a client like a web browser and a web server. First, let’s start with understanding what a standard HTTP web request looks like. Following are a sequence of events for regular HTTP request: Client opens a connection and requests data from the server. The server calculates the response. The server sends the response back to the client on the opened request. HTTP Protocol Ajax Polling Polling is a standard technique used by the vast majority of AJAX applications. The basic idea is that the client repeatedly polls (or requests) a server for data. The client makes a request and waits for the server to respond with data. If no data is available, an empty response is returned. Client opens a connection and requests data from the server using regular HTTP. The requested webpage sends requests to...
    Post a Comment
    Read more

    MonoLithic Vs Microservice Architecture | which Architecture should i choose ?

    From last few years ,microservices are an accelerating trend . Indeed, microservices approach offers tangible benefits including an increase in scalability, flexibility, agility, and other significant advantages. Netflix, Google, Amazon, and other tech leaders have successfully switched from monolithic architecture to microservices. Meanwhile, many companies consider following this example as the most efficient way for business growth. On the contrary, the monolithic approach is a default model for creating a software application. Still, its trend is going down because building a monolithic application poses a number of challenges associated with handling a huge code base, adopting a new technology, scaling, deployment, implementing new changes and others. So is the monolithic approach outdated and should be left in the past? And is it worth shifting the whole application from a monolith to microservices ? Will developing a microservices application help you reach you...
    Post a Comment
    Read more

    Face Detection model on Image/Webcam/Video using Machine Learning OpenCV

    Face detection is a computer technology that is being applied for many different applications that require the identification of human faces in digital images or video. It can be regarded as a specific case of object-class detection, where the task is to find the locations and sizes of all objects in an image that belongs to a given class. The technology is able to detect frontal or near-frontal faces in a photo, regardless of orientation, lighting conditions or skin color . Not Face Recognition! It’s about Detection. Face recognition describes a biometric technology that goes way beyond recognizing when a human face is present. It actually attempts to establish whose face it is. In this article, I’m not going deep into recognizing. I’ll keep that for a future blog article and for the time being, I’m going to explain how to run a simple Face  Detection program using your WebCam with Python Or we can run simple program on image as well . We are dealing with below Cascade models for...
    Post a Comment
    Read more