CAREamics
CAREamics is a PyTorch library aimed at simplifying the use of Noise2Void and its many variants and cousins (CARE, Noise2Noise, N2V2, P(P)N2V, HDN, muSplit etc.).
Why CAREamics?
Noise2Void is a widely used denoising algorithm, and is readily available from the n2v
python package. However, n2v is based on TensorFlow, while more recent methods
denoising methods (PPN2V, DivNoising, HDN) are all implemented in PyTorch, but are
lacking the extra features that would make them usable by the community.
The aim of CAREamics is to provide a PyTorch library reuniting all the latest methods in one package, while providing a simple and consistent API. The library relies on PyTorch Lightning as a back-end. In addition, we will provide extensive documentation and tutorials on how to best apply these methods in a scientific context.
Installation and use
Check out the documentation for installation instructions and guides!
1 maintainer
Metadata
1 maintainer
Release files for careamics 0.3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| careamics-0.3.4.tar.gz | 722.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| careamics-0.3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / careamics-0.3.4.tar.gz
| Download URL | careamics-0.3.4.tar.gz |
|---|---|
| Size | 722.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
32f6bcd399c4fa0fc91ff5151ed3fe32a32beb0f808858383cd4c338026582ca
|
|
BLAKE2b-256 checksum How to use checksums |
eb8357f9895332fe37ac870a9aad2cd55587d15defff28a31886e5b4415e183d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.9.0
|
Release files / careamics-0.3.4-py3-none-any.whl
| Download URL | careamics-0.3.4-py3-none-any.whl |
|---|---|
| Size | 434.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c06eb1929081445bb92b2a5f904d6e7df7badb8f81bdb57205d86f308f0d37ba
|
|
BLAKE2b-256 checksum How to use checksums |
e5f54f2d44c3639904b03eea76d0137da3aa61c959d293b0f4fafdbbe4976c99
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
uv/0.9.0
|
