Image Captioning using CNN ,LSTM and Attention

This is a deeplearning model which tries to summarize an image into a text .

Installation

Install this project with pip3. Use python version 3.7

  pip3 install -R requirements.txt
  python3 app.py

these commands are applicable if you want to try the website in localhost.

you can also install docker and build an image from the docker file and run it.

  docker build -f Dockerfile -t imagecaptioning:api .
  docker run -p 8080:8080 -ti imagecaptioning

Deployment

To deploy this project in google cloud app engine . First create an project in app engine. Install google SDK to push ptojects into your local machine then run the following commands.

  gcloud init
  gcloud app deploy

choose the right project and then push the application to the cloud. This is an monolithic application so a single docker image is complied on the app engine.

Demo

link to demo-https://lucky-dahlia-333406.el.r.appspot.com/index

FAQ

why is this project implimented in tensorflow ?

Tensorflow is actively maintained by google and is very convenient to deploy on a server .It automatically switches to gpu while training if it finds one.

what is BELU score ?

BLEU, or the Bilingual Evaluation Understudy, is a score for comparing a candidate translation of text to one or more reference translations.Although developed for translation, it can be used to evaluate text generated for a suite of natural language processing tasks.

In this project, you will discover the BLEU score for evaluating and scoring candidate text using the NLTK library in Python.

Authors

• @asutoshgha
• @Rupesh-k-yadav

License

MIT