Python library to extract A. Torralba's GIST descriptor.
This is just a wrapper for Lear's GIST implementation written in C. It supports both Python 2 and Python 3 and was tested under Python 2.7.10 and Python 3.4.3 on Linux.
FFTW is required to build lear_gist.
Download lear_gist
sh download-lear.shBuild and install
python setup.py build_ext
python setup.py installIf fftw3f is installed in non-standard path (for example, $HOME/local),
use -I and -L options:
$ python setup.py build_ext -I $HOME/local/include -L $HOME/local/libimport gist
import numpy as np
img = ... # numpy array containing an image
descriptor = gist.extract(img)This sample uses 8 Scene Categories Dataset.
cd sample
sh download-8scene.sh
# Extract GIST features from images in "spatial_envelope_256x256_static_8outdoorcategories" directory and save them into "features" directory
python feature_extraction.py spatial_envelope_256x256_static_8outdoorcategories features
# Train and test a multi-class linear classifier by features in "features" directory
python scene_classification.py features