Fourier Domain Adaption (FDA)
This Python package implements a classic frequency domain adaptation, as shown in:
FDA: Fourier Domain Adaptation for Semantic Segmentation, Yanchao Yang and Stefano Soatto, CVPR 2020
Install with pip
$ python3 -m pip install fda --user
Install from source
$ python3 setup.py install --user
Exemplary code snippet
import fda
# Read source and target images
source_im = cv2.imread('source.jpg')
target_im = cv2.imread('target.jpg')
# Perform domain adaptation
adapted_im = fda.fda(source,_im, target_im, beta=0.005)
Run domain adaptation on a single image
$ python3 -m fda.run --source source.jpg --target target.jpg --output output.jpg --beta 0.005
Some examples of the domain adaptation
| Source image | Target domain image | Beta | Output |
|---|---|---|---|
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0.001 |  |
| 0.01 |  |
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| 0.1 |  |
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0.001 |  |
| 0.01 |  |
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| 0.1 |  |
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0.001 |  |
| 0.01 |  |
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| 0.1 |  |
Run unit tests
$ python3 tests/test_fourier.py
License
This repository is shared under an MIT license.
Author
Luis Carlos Garcia Peraza Herrera (luiscarlos.gph@gmail.com), 2020-2022.
1 maintainer
Metadata
1 maintainer
Release files for fda 0.0.2
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