VisualNN is an online collaborative platform to build, visualize and train deep learning models via a simple drag-and-drop interface. We build it based on Fabrik. It allows researchers to collectively develop and debug models using a web GUI that supports importing, editing and exporting networks to popular frameworks like Caffe, Keras, and TensorFlow.

Installation Instructions

Setting up VisualNN on your local machine is very easy.

1. First set up a virtualenv. Fabrik runs on Python2.7.

   sudo apt-get install python-pip python-dev python-virtualenv
   virtualenv --system-site-packages ~/Fabrik --python=python2.7
   source ~/Fabrik/bin/activate
   

2. Clone the repository via git

   git clone --recursive https://github.com/Cloud-CV/Fabrik.git && cd Fabrik
   

3. Rename settings/dev.sample.py as settings/dev.py and change credentials in settings/dev.py

   cp settings/dev.sample.py settings/dev.py
   

   • Change the hostname to localhost in settings/dev.py line 15. It should now look like this:

   'HOST': os.environ.get("POSTGRES_HOST", 'localhost'), 
   

4. Install redis server

   sudo apt-get install redis-server
   

   • Change the hostname to localhost in settings/common.py line 115.

     "CONFIG": {
         # replace redis hostname to localhost if running on local system
         "hosts": [("localhost", 6379)],
         "prefix": u'fabrik:',
         },
     

   • Replace celery result backend in settings/common.py line 122 with localhost.

     CELERY_RESULT_BACKEND = 'redis://localhost:6379/0'
     

   • Change celery broker URL and result backend hostname to localhost in ide/celery_app.py, line 8.

     app = Celery('app', broker='redis://localhost:6379/0', backend='redis://localhost:6379/0', include=['ide.tasks'])
     

5. If you already have Caffe, Keras and TensorFlow installed on your computer, skip this step.

• For Linux users

  • Install Caffe, Keras and Tensorflow

    cd Fabrik/requirements
    yes Y | sh caffe_tensorflow_keras_install.sh
    

  • Open your ~/.bashrc file and append this line to the end

    export PYTHONPATH=~/caffe/caffe/python:$PYTHONPATH
    

  • Save, exit and then run

    source ~/.bash_profile
    cd ..
    

6. Install dependencies pip install -r requirements/dev.txt

7. Install postgres >= 9.5

• Setup postgres database

  • Start postgresql by typing sudo service postgresql start

  • Now login as user postgres by running sudo -u postgres psql and type the commands below:

    CREATE DATABASE fabrik;
    CREATE USER admin WITH PASSWORD 'fabrik';
    ALTER ROLE admin SET client_encoding TO 'utf8';
    ALTER ROLE admin SET default_transaction_isolation TO 'read committed';
    ALTER ROLE admin SET timezone TO 'UTC';
    ALTER USER admin CREATEDB;
    

  • Exit psql by typing in \q and hitting enter.

• Migrate

  python manage.py makemigrations caffe_app
  python manage.py migrate
  

8. Install node modules

   npm install
   npm install --save-dev json-loader
   sudo npm install -g webpack@1.15.0
   

   • Run the command below in a separate terminal for hot-reloading, i.e. see the changes made to the UI in real time.

   webpack --progress --watch --colors
   

9. Start celery worker

   celery -A ide worker --app=ide.celery_app  --loglevel=info
   

   The celery worker needs to be run in parallel to the django server in a separate terminal.

10. Start django application

    python manage.py runserver
    

    You should now be able to access Fabrik at http://localhost:8000.

Usage

python manage.py runserver

Example

• Use example/tensorflow/GoogleNet.pbtxt for TensorFlow import
• Use example/caffe/GoogleNet.prototxt for Caffe import
• Use example/keras/vgg16.json for Keras import