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

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Travis PyPi

Image Quality


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


  • Python 3.8

  • (Development) Docker


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

pip install image-quality


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 =
>>> brisque.score(img)


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. 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 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  \

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.


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