EvalAI is an open source web application that helps researchers, students and data-scientists to create, collaborate and participate in various AI challenges organized round the globe.
Setting up EvalAI on your local machine is really easy. Follow this guide to setup your development machine.
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Install python 2.x, git, postgresql version >= 9.4, RabbitMQ and virtualenv, in your computer, if you don't have it already. If you are having trouble with postgresql on Windows check this link postgresqlhelp.
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Get the source code on your machine via git.
git clone https://github.com/Cloud-CV/EvalAI.git evalai
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Create a python virtual environment and install python dependencies.
cd evalai virtualenv venv source venv/bin/activate # run this command everytime before working on project pip install -r requirements/dev.txt
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Rename
settings/dev.sample.py
asdev.py
and change credential insettings/dev.py
cp settings/dev.sample.py settings/dev.py
Use your postgres username and password for fields
USER
andPASSWORD
indev.py
file. -
Create an empty postgres database and run database migration.
sudo -i -u (username) createdb evalai python manage.py migrate --settings=settings.dev
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Seed the database with some fake data to work with.
python manage.py seed --settings=settings.dev
This command also creates a
superuser(admin)
, ahost user
and aparticipant user
with following credentials.SUPERUSER- username:
admin
password:password
HOST USER- username:host
password:password
PARTICIPANT USER- username:participant
password:password
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That's it. Now you can run development server at http://127.0.0.1:8000 (for serving backend)
python manage.py runserver --settings=settings.dev
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Open a new terminal window with node(6.9.2) and ruby(gem) install on your machine and type
npm install bower install
If you running npm install behind a proxy server, use
npm config set proxy http://proxy:port
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Now to connect to dev server at http://127.0.0.1:8888 (for serving frontend)
gulp dev:runserver
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That's it, Open web browser and hit the url http://127.0.0.1:8888.
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(Optional) If you want to see the whole game into play, then start the RabbitMQ worker in a new terminal window using the following command that consumes the submissions done for every challenge:
python scripts/workers/submission_worker.py
If you are interested in contributing to EvalAI, follow our contribution guidelines.