Skip to main content

diptorch

Install

pip install diptorch

Hello, World!

import matplotlib.pyplot as plt

from diptorch.filters import gaussian_filter
from diptorch.utils import astronaut, imshow
# Zero-th order Gaussian filter (smoothing)
img = astronaut()
img_filtered = gaussian_filter(img, sigma=2.5)
imshow(img, img_filtered)
plt.show()

# First-order Gaussian filter
img = astronaut()
img_filtered = gaussian_filter(img, sigma=2.5, order=1)
imshow(img, img_filtered)
plt.show()

# Second-order Gaussian filter on the height dimension (y-axis)
img = astronaut()
img_filtered = gaussian_filter(img, sigma=2.5, order=[2, 0])
imshow(img, img_filtered)
plt.show()

Hessian matrix

from diptorch.filters import hessian, hessian_eigenvalues
from einops import rearrange
# Hessian matrix of an image (all second-order partial derivatives)
img = astronaut()
H = hessian(img, sigma=2.5, as_matrix=True)
H = rearrange(H, "B C1 C2 H W -> B (C1 H) (C2 W)").squeeze()

plt.imshow(H, cmap="gray")
plt.axis("off")
plt.show()

# Eigenvalues of the Hessian matrix of an image
# sorted by the magnitude of the eigenvalues
img = astronaut()
eig = hessian_eigenvalues(img, sigma=2.5)
_, axs = imshow(img, *eig.split(1, 1))
axs[1].set(title="Smallest magnitude\neigenvalue")
axs[2].set(title="Largest magnitude\neigenvalue")
plt.show()

Metadata

Release files for diptorch 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for diptorch 0.0.1
File Size Uploaded
diptorch-0.0.1.tar.gz 9.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for diptorch 0.0.1
File Interpreter ABI Platform
diptorch-0.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 18.5 kB

Release files / diptorch-0.0.1.tar.gz

Download URL diptorch-0.0.1.tar.gz
Size 9.8 kB
Tags Source
SHA-256 checksum
How to use checksums
01cb823e7ef783577c245e3d1bde8a5a4dbcc6b51becd5f60a350ed039124937
BLAKE2b-256 checksum
How to use checksums
56bbbe27f171e96c61655c7ef087169672949a2a814426b06f7f97df2127a081
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.12.7

Release files / diptorch-0.0.1-py3-none-any.whl

Download URL diptorch-0.0.1-py3-none-any.whl
Size 8.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
4c03e51d076f594e49170c4f79265ed324afffb0ec888547937c16c9151384b3
BLAKE2b-256 checksum
How to use checksums
13d492cc1bc39a51652f61099534f372ba6b32bec87c1b1529f30d7373c3c9d6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.1 CPython/3.12.7

Release history Release notifications | RSS feed

This release

0.0.1 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page