openfv 0.3.2

computer vision packages in frequency domain

OpenFV

A Python package for computer vision in Frequency Domain.

Installation

You can install the package using pip:

bash

pip install openfv

Usage

• Demo videos: https://www.youtube.com/@sheekjegal/videos

• Here's a basic example of how to use the package:

import cv2 import openfv as fv

Load an image

image = cv2.imread('your_image.png') image2 = cv2.imread('your_image2.png')

Homomorphic filtering

filtered_image = fv.ww_homomorphic_filter(image, d0=30, rh=2.0, rl=0.5, c=2)

Amplitude spectrum calculation

spectrum_image = fv.ww_amplitude_spectrum(image)

Spectral residual saliency map generation

saliency_map = fv.ww_spectral_residual_saliency(image, size=64)

phase congruency edge

edge_map = fv.ww_phase_congruency_edge(image, nscale=4, norient=4,
minWaveLength=3,
mult=1.2,
sigmaOnf=0.9,
k=9.0,
cutOff=0.5,
g=9.0,
epsilon=0.01 )

deblur restoration

restored_image = fv.ww_tikhonov_regularization(image, psf=3, lambda_value=0.01)

phase only correlation

y, x, corr_ratio = fv.ww_phase_only_correlation(image, image2, window=True)

Input

• NumPy array representing an image
• Supports both 2D (grayscale) and 3D (RGB) arrays
• For functions requiring grayscale input (e.g., ww_homomorphic_filter), RGB images must be converted to grayscale.
• For functions supporting RGB input (e.g., ww_amplitude_spectrum), RGB images are processed directly.

Output

• uint8 grayscale image (for most functions)
• Check specific function documentation for exceptions.

Dependencies

• numpy (tested with 1.19.0 or later)
• scipy (tested with 1.15.1 or later)
• cv2 (tested with 4.11.0 or later)

License

This project is licensed under the MIT License - see the LICENSE file for details. Contributing Contributions are welcome! Please feel free to submit a Pull Request.

Author

Wonwoo Park ([e-mail])

Version History

• 0.3.2: phase only correlation added
• 0.3.1: tikhonov_regularization added
• 0.3.0: phase congruency edge added
• 0.2.1: hann window function added in SRSM function
• 0.2.0: spectral residual saliency map added
• 0.1.9: amplitude spectrum added
• 0.1.5: homomorphic filter added
• 0.1.0: Initial release