TorchJPEG
This package contains a C++ extension for pytorch that interfaces with libjpeg to allow for manipulation of low-level JPEG data. By using libjpeg, quantization results are guaranteed to be consistent with other applications, like image viewers or MATLAB, which use libjpeg to compress and decompress images. This is useful because JPEG images can be effected by round-off errors or slight differences in the decompression procedure. Besides this, this library can be used to read and write DCT coefficients, functionality which is not available from other python interfaces.
Besides this, the library includes many utilities related to JPEG compression, many of which are written using native pytorch code meaning they can be differentiated or GPU accelerated. The library currently includes packages related to the DCT, quantization, metrics, and dataset transformations.
LIBJPEG
Currently builds against: libjpeg-9d. libjpeg is statically linked during the build process. See http://www.ijg.org/files/ for libjpeg source.
The full libjpeg source is included with the torchjpeg source code and will be built during the install process (for a source or sdist install).
Install
Packages are hosted on pypi. Install using pip, note that only Linux builds are supported at the moment.
pip install torchjpeg
If there is demand for builds on other platforms it may happen in the future. Also note that the wheel is intended to be compatible with manylinux2014 which means it should work on modern Linux systems, however, because of they way pytorch works, we can't actually build it using all of the manylinux2014 tools. So compliance is not guaranteed and YMMV.
torchjpeg is currently in pre-beta development and consists mostly of converted research code. The public facing API, including any and all names of
parameters and functions, is subject to change at any time. We follow semver for versioning and will adhere to that before making and breaking
changes.
Citation
If you use our code in a publication, we ask that you cite the following paper (bibtex):
Max Ehrlich, Larry Davis, Ser-Nam Lim, and Abhinav Shrivastava. "Quantization Guided JPEG Artifact Correction." In Proceedings of the European Conference on Computer Vision, 2020
Metadata
Release files for torchjpeg 0.9.33
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| torchjpeg-0.9.33.tar.gz | 1.1 MB | Without provenance | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| torchjpeg-0.9.33-cp312-cp312-manylinux2014_x86_64.whl | CPython 3.12 | CPython 3.12 | Linux glibc 2.17+ x86-64 | Details |
| torchjpeg-0.9.33-cp311-cp311-manylinux2014_x86_64.whl | CPython 3.11 | CPython 3.11 | Linux glibc 2.17+ x86-64 | Details |
| torchjpeg-0.9.33-cp310-cp310-manylinux2014_x86_64.whl | CPython 3.10 | CPython 3.10 | Linux glibc 2.17+ x86-64 | Details |
Total release size: 13.9 MB
Release files / torchjpeg-0.9.33.tar.gz
| Download URL | torchjpeg-0.9.33.tar.gz |
|---|---|
| Size | 1.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
aaaa2c8cd93b5a8f4319dbb566f1369bd951ea45f134e9881eddf4ee9fe7e95a
|
|
BLAKE2b-256 checksum How to use checksums |
c3d81a8ff6a295bd1846815ab3db5edf7f2a5fa4a8f822c1fdedffdf07f99148
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.12.5 Linux/5.15.154+
|
Release files / torchjpeg-0.9.33-cp312-cp312-manylinux2014_x86_64.whl
| Download URL | torchjpeg-0.9.33-cp312-cp312-manylinux2014_x86_64.whl |
|---|---|
| Size | 4.3 MB |
| Tags | CPython 3.12 Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
413be5a87e44a31a8fe9fa8a7376ff87388c615b89c34beb482eb1f3c50ebc07
|
|
BLAKE2b-256 checksum How to use checksums |
4ddb642573da3f0111af8260857003d4aefa284253c0d3536cdb1d3279f3c7ce
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.12.5 Linux/5.15.154+
|
Release files / torchjpeg-0.9.33-cp311-cp311-manylinux2014_x86_64.whl
| Download URL | torchjpeg-0.9.33-cp311-cp311-manylinux2014_x86_64.whl |
|---|---|
| Size | 4.3 MB |
| Tags | CPython 3.11 Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
c6c6f5dcdc765cbecd1ec2016cc152ad5dfb1db189fb307902d336b87ed7c0f5
|
|
BLAKE2b-256 checksum How to use checksums |
1d8962b75b8220e156326a4fbbcc9c605fb5c71f351566df2f300dc748359133
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.12.5 Linux/5.15.154+
|
Release files / torchjpeg-0.9.33-cp310-cp310-manylinux2014_x86_64.whl
| Download URL | torchjpeg-0.9.33-cp310-cp310-manylinux2014_x86_64.whl |
|---|---|
| Size | 4.3 MB |
| Tags | CPython 3.10 Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
61d818badc4bb72b99bec611e9015ad686ed942c40f15975a613e920edf63337
|
|
BLAKE2b-256 checksum How to use checksums |
8bb716fa63854fd94aefed207cd8979992d491331e8e73a179e0c0a84c87c553
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.12.5 Linux/5.15.154+
|
Security for torchjpeg 0.9.33
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.