Quiver
Interactive convnet features visualization for Keras
The quiver workflow
-
Build your model in keras
model = Model(...)
-
Launch the visualization dashboard with 1 line of code
quiver_engine.server.launch(model, input_folder='./imgs')
-
Explore layer activations on all the different images in your input folder.
Quickstart
Installation
pip install quiver_engine
Usage
Take your keras model
, launching Quiver is a one-liner.
from quiver_engine import server
server.launch(model)
This will launch the visualization at localhost:5000
Options
server.launch(
model, # a Keras Model
# where to store temporary files generatedby quiver (e.g. image files of layers)
temp_folder='./tmp',
# a folder where input images are stored
input_folder='./',
# the localhost port the dashboard is to be served on
port=5000
)
Development
Building from master
Check out this repository and run
python setup.py develop
Building the Client
cd quiverboard
npm install
export QUIVER_URL=localhost:5000 # or whatever you set your port to be
npm start
Credits
- This is essentially an implementation of some ideas of deepvis and related works.
- A lot of the pre/pos/de processing code was taken from here and other writings of fchollet.
- The dashboard makes use of react-redux-starter-kit