FoveaTorch 👀🔥 
Differentiable foveated vision for Deep Learning methods
References
- J.S. Perry and W.S. Geisler, "Gaze-contingent real-time simulation of arbitrary visual fields", IS&T/SPIE Electronic Imaging, 2002
- M. Jiang, S. Huang, J. Duan and Q. Zhao, "SALICON: Saliency in Context", IEEE Conference on Computer Vision and Pattern Recognition, 2015
- Zhibo Yang, "Image_Foveation_Python: Python implementation of image retina transformation"
Metadata
Release files for foveatorch 0.1.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| foveatorch-0.1.8.tar.gz | 7.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| foveatorch-0.1.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.3 kB
Release files / foveatorch-0.1.8.tar.gz
| Download URL | foveatorch-0.1.8.tar.gz |
|---|---|
| Size | 7.1 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/5.1.1 CPython/3.12.7
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Release files / foveatorch-0.1.8-py3-none-any.whl
| Download URL | foveatorch-0.1.8-py3-none-any.whl |
|---|---|
| Size | 8.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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twine/5.1.1 CPython/3.12.7
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