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Image quality is an open source software library for Automatic Image Quality Assessment (IQA).

Project description

Travis PyPi

Image Quality

Description

Image quality is an open source software library for Automatic Image Quality Assessment (IQA).

Dependencies

  • Python 3.8

  • (Development) Docker

Installation

The package is public and is hosted in PyPi repository. To install it in your machine run

pip install image-quality

Example

After installing image-quality package, you can test that it was successfully installed running the following commands in a python terminal.

>>> import imquality.brisque as brisque
>>> import PIL.Image

>>> path = 'path/to/image'
>>> img = PIL.Image.open(path)
>>> brisque.score(img)
4.9541572815704455

Development

In case of adding a new tensorflow dataset or modifying the location of a zip file, it is necessary to update the url checksums. You can find the instructions in the following tensorflow documentation.

The steps to create the url checksums are the following:

1. Take the file with the dataset configuration (e.g. live_iqa.py) an place it in the tensorflow_datasets folder. The folder is commonly placed in ${HOME}/.local/lib/python3.8/site-packages if you install the python packages using the user flag.

2. Modify the __init__.py of the tensorflow_datasets to import your new dataset. For example from .image.live_iqa import LiveIQA at the top of the file.

3. In your terminal run the commands:

touch url_checksums/live_iqa.txt
python -m tensorflow_datasets.scripts.download_and_prepare  \
   --register_checksums  \
   --datasets=live_iqa

4. The file live_iqa.txt is going to contain the checksum. Now you can copy and paste it to your project’s url_checksums folder.

Maintainer

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