Python module with functions for image feature extraction based on the OpenCV Python bindings.
- OpenCV (w/ Python bindings:
sudo apt-get install python-opencv)- Python Image Library
pip install https://github.com/johaness/bifl.git
The features.extract function allows extraction of all available features
on different spatial scales -- see the source documentation for details.
The bifl command line script accepts any number of image file names as
parameter, runs features.extract on every image, stores results in
a pickle file of cvMat matrices, and renders each feature into a PNG
image.
The other modules contain a number of support functions useful for working with OpenCV data structures.
Image features implemented in pure Python are defined in mods.py:
contrast(inmat, ws = 51) smooth(inmat, ws = 51) sobel(inmat, ws = 7) pyrdown(inmat) pyrsdown(*inmats) pyrup(inmat) zscale(inmat) equalize(inmat) add(*mats) addZ(*mats) multiply(inmat, value) addZW(inmats, weights) addW(inmats, weights) spatialbias(inmat, biasmat, (x, y), base=1.0, gain=1.0, bias_zero=None) maxior(inmat, steps=10, inhibition=0.2, radius=90)
Image features can be implemented in C with a minimal wrapper below
bifl/cpy/:
# split RGB into RG, BY, Lum, Sat colorsplit(inimage) # intrinsic dimensionality intdim(inmat)
BSD License, see LICENSE file
Development sponsored by WhiteMatter Labs GmbH, creators of EyeQuant.