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 = PIL.Image.open(path)
>>> brisque.score(img)
4.9541572815704455
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.