tf-spherical-hashing
Advanced tools
A Tensorflow 2 implementation of Spherical Hashing.
Spherical hashing is a way to compute a binary encoding of a feature vector while still maintaining spatial coherence. This binary encoding can then be used for an approximate nearest neighbor solution since the compactness of this representation allows for faster neighbor search.
from spherical_hashing import train_spherical_hashing
import tensorflow as tf
x_train = tf.random.uniform(shape=(1000, 512), minval=-10.0, maxval=10.0)
sph_model = train_spherical_hashing_model(x_train, n_bits=32)
x_test = tf.random.uniform(shape=(100, 512), minval=-10.0, maxval=10.0)
bits = sph_model(x_test, apply_pack_bits=True)
pip install tf-spherical-hashing
./scripts/run-tests.sh
./scripts/publish.sh
FAQs
Tensorflow implementation of Spherical Hashing.
We found that tf-spherical-hashing demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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