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.
Sponsor
