Skip to main content

3D variants of popular models for segmentation like FPN, Unet, Linknet etc using Pytorch module.Automatic conversion of 2D imagenet weights to 3D variant

Metadata

Release files for segmentation-models-pytorch-3d 1.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for segmentation-models-pytorch-3d 1.0.2
File Size Uploaded Provenance
segmentation_models_pytorch_3d-1.0.2.tar.gz 77.3 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for segmentation-models-pytorch-3d 1.0.2
File Interpreter ABI Platform
segmentation_models_pytorch_3d-1.0.2-py3-none-any.whl Python 3 none any Details

Total release size: 198.3 kB

Release files / segmentation_models_pytorch_3d-1.0.2.tar.gz

Download URL segmentation_models_pytorch_3d-1.0.2.tar.gz
Size 77.3 kB
Tags Source
SHA-256 checksum
How to use checksums
44bb3aba390c78af574d9b880517dd66da992f7f2c8b89099c000ef181a343c3
BLAKE2b-256 checksum
How to use checksums
1de46bee4244bc7c44c31f33b65c13fa3dac2cb826dbd9de224292cb52c25894
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.8.3

Release files / segmentation_models_pytorch_3d-1.0.2-py3-none-any.whl

Download URL segmentation_models_pytorch_3d-1.0.2-py3-none-any.whl
Size 121.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
9510ded43a7bb0ff3b1776fedfbd101a3ba2b19f92d0032d66d6025d4b494bbd
BLAKE2b-256 checksum
How to use checksums
b7433b27f541d9b391c8c51e87947ff93f901c12dd9048a4415bbd97df8ee62c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.8.3

Security for segmentation-models-pytorch-3d 1.0.2

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.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page