Open Source Hack

Open Source Hack is a 1-month long virtual open source program by AnitaB.org Open Source Community. This program aims to help participants begin contributing to various Open Source Projects by highlighting non-coding paths to contribute to open source. Top participants (maximum merged PRs) will get a small gift card in addition to the digital certificate.


Open Source Hack

Open Source Hack is a 1-month long virtual open source program by AnitaB.org Open Source Community. This program aims to help participants begin contributing to various Open Source Projects by highlighting non-coding paths to contribute to open source. Top participants (maximum merged PRs) will get a small gift card in addition to the digital certificate.


If you can’t fly, then run. If you can’t run, then walk. If you can’t walk, then crawl, but by all means, keep moving . — Martin Luther King Jr.

Open Source Hack

Open Source Hack is a 1-month long virtual open source program by AnitaB.org Open Source Community. This program aims to help participants begin contributing to various Open Source Projects by highlighting non-coding paths to contribute to open source. Top participants (maximum merged PRs) will get a small gift card in addition to the digital certificate.


If you can’t fly, then run. If you can’t run, then walk. If you can’t walk, then crawl, but by all means, keep moving . — Martin Luther King Jr.

STUDENT CODE-IN : A Step Towards Open Source!


This Article is the 2nd part of Face Recognition & Image Classification App, I have build this App to help Blind & visually impaired classify objects.

Please do refer to the 1st part .

Increasing the accuracy & classes

To increase the accuracy I have used clear, precise & more number of images in the data set. In the 1st part of the App I have used 3 classes for classification but now I have increased the number of classes to 13.

Data set


In this article you’ll learn how to convert text into natural sounding speech using Python.

Speech Synthesis

The process of translating text input into audio data is called synthesis and the output of synthesis is called synthetic speech. Text-to-Speech takes two types of input: raw text or SSML-formatted data.

Text-to-Speech


Face Verification vs. Face Recognition

Verification (1:1 problem)

  1. Input image, name/ID
  2. Output whether the input image is that of the claimed person

Recognition (1:K problem)

  1. Has a database of K persons
  2. Get an input image
  3. Output ID if the image is any of the K persons (or “not recognized”)

Recognition is much harder the the verification.

Developer Tools & Technologies used for building the App

  1. Teachable Machine (https://teachablemachine.withgoogle.com/)
  2. TensorFlow Lite
  3. Android Studio (Version used 4.0.0)

Steps for Building the TensorFlow Lite Android App

Step 1

What is Teachable Machine?

If you’re not an expert at Coding don’t worry . Teachable Machine is a web-based tool that makes creating machine learning models fast, easy, and accessible to everyone. Train a computer to recognize your own…

Ashwini Jha

Open Source Enthusiast | GSSoC’20 | Student Code-in’20

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