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Image classification using Tensorflow (Inception v3)

Home Page: http://tf-classify.herokuapp.com

Python 52.35% CSS 15.44% JavaScript 14.44% HTML 17.77%

image-classify-server's Introduction

ImageClassification-Server

Image classification with Web API and UI.
It's is written in Django along with Tensorflow uing Google's Inception v3 model
The web interface is made using materializecss and jQuery
It is extension of this project.

Web Interface

The Web Interface can be found at http://tf-classify.herokuapp.com

Web API

You can classify using web API by sending a POST request at http://tf-classify.herokuapp.com/classify_image/classify/api/

Input

Parameter Type Description
image file Image file that you want to classify.
image64 text Image in base64 form that you want to classify. Currently supports JPEG images only
k text
(optional, default=10)
Return top-k categories of the results. Must me string in integer format.

Note: you need to send either 'image' or 'image64'

Result

Parameter Type Description
success bool Whether classification was sucessfuly or not
confidence category, float pair of category and it's confidence

Note: category is not paramater name but string of the category.
Example: {"success": true, "confidence": { "mongoose": 0.87896, "hare": 0.00123 }}

Using Retrained Inception Model

  • Retrain the model using your images. Refer here.
  • Fork this repo
  • Replace the generated graph and label files in /classify_image/inception_model/
  • Deploy the Django project

Contribute

I am just beginner. If you find any bugs or want to improve the project, fell free to do it uisng pull request.

image-classify-server's People

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