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speks7 / nazar

Electronic component detection, identification and recognition system in realtime from camera image using react-native and tensorflow for classification along with Clarifai API with option to search the component details from web with description shown from Octopart fetched from server
https://play.google.com/store/apps/details?id=com.speks.nazar
Apache License 2.0
33 stars 9 forks source link
android base64 camera clarifai-api flask heroku image inception ios mobile octopart octopart-api python react react-native realtime tensorflow tensorflow-classification

readme

Nazar

icon

Electronic component detection system with server: Nazar Server

Overview

Nazar is an app built with react-native with a little spice of Tensorflow InveptionV3 which allows the user to take a picture using the camera or fetch image from gallery to identify the component with the predicted percentage ratio, thus using image processing and algorithm to segment them after detection along with fetching description about the detected component using Octopart API whose response is sent from the nazar-server itself.

It is done with both Clarifai API and Tensorflow frozen graph server deployed in heroku to deduce with internet along with option to look for feeds from internet within the app. The Option to fetch the details about detected component is setup but needs furnishing.

Run both on iOS and Android

Demo

Nazar demo

Information

    

Main View Image Picker Online analysis Realtime Analysis

Installation

Clone the source locally:

$ git clone https://github.com/aryaminus/nazar
$ cd nazar

Start the application in development mode

npm install
react-native link
react-native run-android
react-native run-ios

or for VS-Code:

npm install
react-native link

then press F1 or Fn+F1 and React Native:Run Android on Device or React Native:Run iOS on Simulator

References

  1. react-native-live-translator
  2. seepizz
  3. tensorflow-for-poets
  4. Generate Signed APK

Contributing

  1. Fork it (https://github.com/aryaminus/nazar/fork)
  2. Create your feature branch (git checkout -b feature/fooBar)
  3. Commit your changes (git commit -am 'Add some fooBar')
  4. Push to the branch (git push origin feature/fooBar)
  5. Create a new Pull Request