Extract identity vector for individual faces
Here I am going to discuss how to extract the face encoding or face embedding from an image using pre-trained models that are available in open source. I have also attached the code refer this git.
It analyses the given image and returns numerical vectors that represent each detected face in the image.The vectors of different size 64,128,256,512. Here we are going to discuss the model which returns a vector of 128 sizes.
We can use this embedding we can able to perform face recognition and face verification and face Matching Application.
Here we discuss a few available and most used face detection deep learning-based models and their performance concerning the accuracy and computational cost.
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real-world problems. It conveniently has the necessary bindings that will enable you to run many tasks directly in Python. One of them we are going to try is Face Detection. To install Dlib follow the link.
Dlib offers different algorithms for face detection. One of them is a frontal face detector which works well. The detector is…
As developers we love to write code,but what about documenting it ?
Being a developer we might read more about the code than what we write. So it is very frustrating to read badly documented code/scripts.
As a developer we need to read lots of documentation of library/frameworks and our colleague’s code.
Similarly, if someone wants to read your code then it requires documentation so they can understand the code in a better way.
Generally, programmers like us, won’t like to document the process. But we add comments for our codes, which will help us refer to the functionality at…
Imitate Human Activities with Machine
I like to share my tool which is developed in order to imitate human interaction with machine.
It is a lightweight, customizable and OS independent application.
Here I have attached the Git link of this tool, where you can find the scripts and its installation steps.
Before that, you need to know what the tool can do and how its works and where we can use it.
The tool is used to replicate human action against machine which means it will listen to human behaviour with machine and execute it in same order and same…
Figure out quality and quantity of the feature from Data
Actually the success of all Machine Learning algorithms depends on how you present the data.
This is the continuation of my previous post. In this post, we are going to deal with the theory behind feature engineering.
Features in data refers to columns. It is the process of transforming the given data into a new form which is easy to interpret and understand. It is an important phase in the pipeline of building a ML model, since it creates a difference between a good and bad model. …
Sequence of phases that a data science project goes through
If you plan to do a data science project, it is important to understand the various phases and stages that the project undergoes. It may be any project in Machine Learning or Deep Learning. The steps involved are listed below.
Data is the primary raw material for any machine learning project. How and where do we get the data?
It is the technique used to extract the data from websites and store it in local storage for later use. It can be done either manually or in an…
In this post let’s explore regression algorithm and script it from scratch in python and R.
Linear regression is a simple and easy algorithm used in machine learning for predictive analysis. It is used to establish a relationship between an input variable(X) and output variable(Y). Input with single independent variable is predominantly called as linear regression and input with more than one independent variable is called as multiple linear regression.
The input variable is the independent variable and output variable is the dependent variable.
Equation of the line,
Y=b0 + b1.X
where b1 is the slope of the line and…
Here, I would like to share, how to setup Nvidia, cuDNN & CUDA drivers for Deep Learning Applications for both local machines as well for cloud based applications in Linux platform.
Once your machine/instance is launched , initially update & upgrade the machine.
sudo apt-get update
sudo apt-get upgrade
Install the basic dependencies like cmake ,git.
sudo apt-get install build-essential
sudo apt-get install cmake git wget
Post which, you need to verify that your machine can support NVIDIA drivers using this command. If your machine is not compatible with NVIDIA drivers, perform the same steps on a different machine/instance.
Decorators can be thought of as functions which modify the functionality of another function. It is a clean way of adding extra functionality to functions by using the “@” symbol. Also, it is a function which will accept another function as its parameter.
Python uses the keyword called “def” to declare a function in it ,which stands for definition. The sample code is ,
>>> def medium():
... print("Hello Medium!")
Here I have created a function called medium() which will print a statement “Hello Medium!”
In case of adding new features to this above function…