Image search engine powered by Django
Clone the repo
# SSH
git clone git@github.com:bisoncorps/imageQ.git
# HTTPS
git clone https://github.com/bisoncorps/imageQ.git
Activate virtual environment. All project work should be done in virtualenvs and virtualenv names must be added to gitignore
- You could easily run from project directory to setup project or follow through
make
- Install the requirements
# install pipenv
sudo pip3 install pipenv
# install requirements
pipenv install
Install Postgres
sudo apt-get install postgresql postgresql-contrib postgis
Create Postgres User
sudo su postgres -c "psql -c \"CREATE USER imageq WITH PASSWORD 'imageq';\""
sudo su postgres -c "psql -c \"CREATE DATABASE imageqdb OWNER imageq;\""
sudo su postgres -c "psql -d imageqdb -c \"CREATE EXTENSION IF NOT EXISTS postgis;\""
sudo su postgres -c "psql -d imageqdb -c \"CREATE EXTENSION IF NOT EXISTS postgis_topology;\""
Run migrations before starting the django-server
python manage.py migrate
To view the API locally on port 9000
python manage.py runserver 9000
The prediction API code can be found at the repo
The master
branch of the repo is linked to automatically deployed
and it sends requests to the deployed prediction API
-
Go to ImageQ Search Engine
-
Select an upload mode from dropdown i.e. (
Image URL
/Upload
/Camera(mobile)
) -
Select search engine to use i.e. (
Google
/Yahoo
/Bing
) -
Click
Search!
button
Code Documentation is available on Github Pages
All important production settings are in the ImageQ.settings.production.py
file.
Settings should be inherited from ImageQ.settings.common.py
for development or used as it is
To change from local settings to production settings and vice-versa, change current_settings
variable in ImageQ.wsgi.py
accordingly
All Celery async tasks are located in tasks.py
of each app file in each app directory
See TODO