This is a deeplearning model which tries to summarize an image into a text.
Install this project with pip3. Use python version 3.7
pip3 install -R requirements.txt
python3 app.pythese 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 imagecaptioningTo deploy this project in google cloud app engine. First create an project in app engine. Install google SDK to push projects into your local machine then run the following commands.
gcloud init
gcloud app deploychoose 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.
link to demo-https://lucky-dahlia-333406.el.r.appspot.com/index
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.
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.