semvec/pypi-packages huggingface dataset:
userpath 1.9.2
Cross-platform tool for adding locations to the user PATH
Requires Python: >=3.7
Keywords: path,user path

# userpath

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-----

This is a tool for modifying a user's `PATH`.

**Table of Contents**

- [Installation](#installation)
- [CLI](#cli)
- [API](#api)
- [License](#license)

## Installation

```console
pip install userpath
```

## CLI

```console
$ userpath -h
Usage: userpath [OPTIONS] COMMAND [ARGS]...

Options:
  --version   Show the version and exit.
  -h, --help  Show this message and exit.

Commands:
  append   Appends to the user PATH
  prepend  Prepends to the user PATH
  verify   Checks if locations are in the user PATH
```

## API

```pycon
>>> import userpath
>>> location = r'C:\Users\Ofek\Desktop\test'
>>>
>>> userpath.in_current_path(location)
False
>>> userpath.in_new_path(location)
False
>>> userpath.append(location)
True
>>> userpath.in_new_path(location)
True
>>> userpath.need_shell_restart(location)
True
```

## License

`userpath` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
image-classification-package 0.0.11
This package includes all the necessary components to classify images using a pre-trained models.
Requires Python: >=3.8
Keywords: dashai,image classification,package,pytorch,torchvision

# **Image Classification Package**

This package include all the necessary components (Task, Models, Dataloader) to perform image classification task.

## **Task**

**ImageClassificationTask**

The task of this package is to perform image classification. The task is defined in the `image_classification_task.py` file. The task is to classify the images into different classes. The task is defined as a class `ImageClassificationTask` which is inherited from the `BaseTask`.

## **Dataloader**

**ImageDataLoader**

This module is a dataloader for the images. The module is defined in the `image_dataloader.py` file. The module is defined as a class `ImageDataLoader` which is inherited from the `BaseDataLoader`. The module uses the `load_dataset` method from the library `datasets` to load the dataset.

## **Models**

**BasicFinetunnedModels**

This module is a image classification model which uses the pre-trained models from the `torchvision.models` and finetunes them on the given dataset. The module is defined in the `basic_finetunned_models.py` file. The module is defined as a class `BasicFinetunnedModels` which is inherited from the `ImageClassificationModel`.

The pretrained models available are:

- resnet18
- resnet34
- resnext50_32x4d
- vgg16
- maxvit_t
- densenet121
- efficientnet_b0
- googlenet
- mnasnet0_5
- mobilenet_v2
- regnet_x_16gf