Metadata-Version: 2.1
Name: piqa
Version: 1.0.1
Summary: PyTorch Image Quality Assessment
Home-page: https://github.com/francois-rozet/piqa
Author: François Rozet
Author-email: francois.rozet@outlook.com
License: UNKNOWN
Description: # PyTorch Image Quality Assessment
        
        This package is a collection of measures and metrics for image quality assessment in various image processing tasks such as denoising, super-resolution, image interpolation, etc. It relies heavily on [PyTorch](https://github.com/pytorch/pytorch) and takes advantage of its efficiency and automatic differentiation.
        
        It should noted that `piqa` is directly inspired from the [`piq`](https://github.com/photosynthesis-team/piq) project. However, it focuses on the conciseness, readability and understandability of its (sub-)modules, such that anyone can freely and easily reuse and/or adapt them to its needs.
        
        > `piqa` should be pronounced *pika* (like Pikachu ⚡️)
        
        ## Installation
        
        The `piqa` package is available on [PyPI](https://pypi.org/project/piqa/), which means it is installable with `pip`:
        
        ```bash
        pip install piqa
        ```
        
        Alternatively, if you need the lastest features, you can install it using
        
        ```bash
        git clone https://github.com/francois-rozet/piqa
        cd piqa
        python setup.py install
        ```
        
        or copy the package directly to your project, with
        
        ```bash
        git clone https://github.com/francois-rozet/piqa
        cd piqa
        cp -R piqa <path/to/project>/piqa
        ```
        
        ## Getting started
        
        ```python
        import torch
        import piqa.psnr as psnr
        import piqa.ssim as ssim
        
        x = torch.rand(3, 3, 256, 256)
        y = torch.rand(3, 3, 256, 256)
        
        # PSNR function
        l = psnr.psnr(x, y)
        
        # SSIM instantiable object
        criterion = ssim.SSIM().cuda()
        l = criterion(x, y)
        ```
        
        ## Documentation
        
        The [documentation](https://francois-rozet.github.io/piqa/) of this package is generated automatically using [`pdoc`](https://github.com/pdoc3/pdoc).
        
        > The code follows the [Google Python style](https://google.github.io/styleguide/pyguide.html) and is compliant with [YAPF](https://github.com/google/yapf).
        
Keywords: pytorch image processing metrics
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
