semvec/pypi-packages huggingface dataset:
decavision 1.4.2
A package to easily train powerful image classification models using colab's free TPUs.
Requires Python: >=3.6

The AI team at Décathlon Canada developed a library to help with the training of image
                        classification models. It is specially made to exploit the free TPUs that are offered
                        in Google colab notebooks. You can find the full documentation
                        [here](https://decavision-doc.herokuapp.com/)

                        ## Version 1.4.2
                        Update dependencies and testing functions

                        ## Version 1.4.1
                        Fix hyperparameter optimization for multilabel

                        ## Version 1.4.0
                        Added multilabel classification

                        ## Version 1.3.0
                        Use suggested image sizes
                        Add EfficientNetV2 models

                        ## Version 1.2.1
                        Change to Tensorflow 2.5

                        ## Version 1.2.0
                        Add semi-supervised learning features

                        ## Version 1.1.3
                        Link to public repository

                        ## Version 1.1.2
                        Change name of package

                        ## Version 1.1.1
                        Fix typo in split_train

                        ## Version 1.1.0
                        Remove google scraping

                        ## Version 1.0.0
                        Original release
protectonce-native 0.1.28b2
python agent interface native package

# Agent Native - Packaging
## Requirements
Build Mininmum Requirements:
- Python3

## Packaging
Run `packaging.sh` 
Check whether the core folder contain `core.js` and out folder contain `libagent.so` in root.
if above files are not present in respective folders
run `packaging.sh` again.

After that run `setup.py`
it will generate the `.whl` package