Skip to main content

UDNN

Project description

UDNN

A Convolutional Neural Network for fast upscaling of low-resolution sinograms in x-ray CT time-series

To install visit first the Pytorch website (https://pytorch.org/get-started/locally/) to manually install the correct version depending on the OS, Python and CUDA version you are using.

Then install either via pip:

pip install udnn

Or using conda:

conda install -c dimitriosbellos udnn

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

udnn-0.0.3.tar.gz (11.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

udnn-0.0.3-py3-none-any.whl (13.7 kB view details)

Uploaded Python 3

File details

Details for the file udnn-0.0.3.tar.gz.

File metadata

  • Download URL: udnn-0.0.3.tar.gz
  • Upload date:
  • Size: 11.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.25.1 requests-toolbelt/0.9.1 urllib3/1.26.6 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.5

File hashes

Hashes for udnn-0.0.3.tar.gz
Algorithm Hash digest
SHA256 e92f24704b70b0fbcd5389a7af30f743850a8855bf9ef6f4dba7d2757dd2e8ae
MD5 452726027770f06d7c0fc51d2a5565ea
BLAKE2b-256 d6c54f1a05083cdf252a1bef176c3873798bc4a295a0d709a3fcfb2d1f9682b4

See more details on using hashes here.

File details

Details for the file udnn-0.0.3-py3-none-any.whl.

File metadata

  • Download URL: udnn-0.0.3-py3-none-any.whl
  • Upload date:
  • Size: 13.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.25.1 requests-toolbelt/0.9.1 urllib3/1.26.6 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.5

File hashes

Hashes for udnn-0.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 ece9a6f38140d6e9acf78299073cd729951f36e85c426e4e1da5288b609c4696
MD5 408cacee8b14aa9fdfcc9117cb67ed61
BLAKE2b-256 5292218337b0c07170030500e3efcb1b7f6c54eab308000414612abccd454f9e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page