FastHOG
Reasonably fast implementation of Histogram of Oriented Gradients. Designed to be roughly equivalent to
skimage.feature.hog. While slightly less flexible (it only supports float64 single-channel images),
it is significantly faster, so ideal in workloads where HOG calculation is a bottleneck, as was in
the https://github.com/flatironinstitute/ManifoldEM project that inspired this repository.
Installation
pip install fasthog
Usage
Example taken from https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_hog.html
from fasthog import hog
from skimage import data
from skimage.color import rgb2gray
image = rgb2gray(data.astronaut())
fd, hog_image = hog(
image,
n_bins=8,
pixels_per_cell=(16, 16),
cells_per_block=(1, 1),
)
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 4), sharex=True, sharey=True)
ax1.axis('off')
ax1.imshow(image, cmap=plt.cm.gray)
ax1.set_title('Input image')
# Rescale histogram for better display
hog_image_rescaled = exposure.rescale_intensity(hog_image, in_range=(0, 10))
ax2.axis('off')
ax2.imshow(hog_image_rescaled, cmap=plt.cm.gray)
ax2.set_title('Histogram of Oriented Gradients')
plt.show()
Metadata
Release files for fasthog 0.1.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
Total release size: 8.3 MB
Release files / fasthog-0.1.7-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Release files / fasthog-0.1.7-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Release files / fasthog-0.1.7-pp39-pypy39_pp73-macosx_11_0_arm64.whl
| Download URL | fasthog-0.1.7-pp39-pypy39_pp73-macosx_11_0_arm64.whl |
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| Download URL | fasthog-0.1.7-pp38-pypy38_pp73-macosx_11_0_arm64.whl |
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twine/6.1.0 CPython/3.10.13
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Release files / fasthog-0.1.7-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | fasthog-0.1.7-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
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| Size | 16.5 kB |
| Tags | CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.17+ x86-64 |
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SHA-256 checksum How to use checksums |
6f7081c763341e8e6587acca5d7f71ab71988629895574447f1d3807faf691c0
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twine/6.1.0 CPython/3.10.13
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