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<h2><p align="center">Shared utility functions powering Moonshine tools.</p></h2>
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<br />
## What is Mash?
Mash is a straightforward utility library for common tasks in computer vision and deep model training. The library was broken out of previous Moonshine projects like Moonshine and Zeroshot.
## What can Mash Do?
Mash broadly supports a few utilities, but the main ones are:
1. Easy image conversion: simply call `to_pil`, `to_numpy`, and `to_tensor` to convert image formats. Accepts other images, URLs, or local files.
2. Image processing files: convenience functions like `crop_to_multiple_of_dimensions` for transformer based patch models like ViT.
3. Console UI: for long running jobs, a fullscreen console utility that has a progress bar at the bottom and text logging.
4. Cloud functions: use `glob` or `exists` on AWS or GCS links.
For a complete list of functions, see [the documentation](https://moonshine-mash.readthedocs.io/en/latest/index.html)
## Installation
To install via pip:
`pip install mashlib`
## Usage
To use:
```python
# Import base package
import mash
# Import image processing
import mash.images as mi
image = mi.to_numpy("/path/to/image.png")
```
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