Package for doing a simple Fourier-based domain adaptation.
Project description
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 |
---|---|---|---|
0.001 | |||
0.01 | |||
0.1 | |||
0.001 | |||
0.01 | |||
0.1 | |||
0.001 | |||
0.01 | |||
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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
fda-0.0.2.tar.gz
(5.4 kB
view details)
File details
Details for the file fda-0.0.2.tar.gz
.
File metadata
- Download URL: fda-0.0.2.tar.gz
- Upload date:
- Size: 5.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.2.0 pkginfo/1.4.2 requests/2.27.1 setuptools/62.3.1 requests-toolbelt/0.8.0 tqdm/4.48.2 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 98909787906edd7df7fa27e61236c75f67e37656cd830d4f3d1211c8894ff28b |
|
MD5 | 6cfaf3976d571e53747ce97f22d49fb2 |
|
BLAKE2b-256 | 2f6e0f0bd795ea11cad9e1596acfd6772df0a19de697d807813ca7f21d16550f |