Segmentools provide low and high levels utilities to train, evaluate and deploy models. Low levels classes and functions are usefull develop new method while keeping data formats uniforms and high level classes allow to write scripts in a very concise and understable way.
Project description
Segmentools
Torch overlay for trainning and inference processes for semantic segmentation tasks.
💪 Context
Segmentools is developped by INRAE (french National Research Institute for Agriculture, Food and the Environment) for the PHENOME-EMPHASIS project
Install
Segmentools has mostly been tested under Python 3.10 (even if it should work with later versions). We recommend using 3.10.
In your python environment run
pip install segmentools
Code access and documentation
Source code documentation will be accessible soon.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file segmentools-0.1.0.tar.gz.
File metadata
- Download URL: segmentools-0.1.0.tar.gz
- Upload date:
- Size: 23.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
77a238c7c22cfc62f0f77a0437b7c67eb7aba8607ed64d95bee02d0f3963f421
|
|
| MD5 |
e66e05bca43b52458a2f4a9803ebadb3
|
|
| BLAKE2b-256 |
7c92e793fceb564f9ffd0cdca52519558e7e340f343d1369a167c7f11f48f932
|
File details
Details for the file segmentools-0.1.0-py3-none-any.whl.
File metadata
- Download URL: segmentools-0.1.0-py3-none-any.whl
- Upload date:
- Size: 26.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
edf7559964e67ffc054b50fd3f7af3d7c0bd2e7425c690de8c7de138a53557f0
|
|
| MD5 |
bef37cad0f141b1efb2aa98ff1bd3c6a
|
|
| BLAKE2b-256 |
d8f56da5543292134444118a848078c63624000f65c2661bc67beef8cca68c7d
|
