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CHIPQA-0: No-Reference Video Quality Assessment using Space-Time Chips

ChipQA-0 is a prototype version of ChipQA. You can read ChipQA-0 here: https://ieeexplore.ieee.org/abstract/document/9287151.

This repository contains code for ChipQA-0. Code for ChipQA is available here: https://github.com/JoshuaEbenezer/ChipQA.

Requirements

See requirements.txt

Feature extraction

To extract features, run


python3 chipqa0.py path/to/input_folder path/to/output_folder

input_folder must contain the videos from which chipqa features will be extracted. output_folder will contain the features that are written out.

Training with LIVE-APV Livestream VQA database

After extracting the features, run


python3 zip_feats_and_scores.py input_folder csv_file output_file 

Here input_folder must contain the features generated from the previous step, csv_file must be a csv file with LIVE-APV database names and scores, and output_file will be where the combined features and scores will be stored.

After this, run


python3 svr.py input_file output_folder

to evaluate. input_file must be the path where the zipped features and scores are saved. The predictions and the ground truth MOS for each of the runs will be stored in output_folder.

all_srocc.m can then be used to find the SROCC and LCC.

If you use the code here, please cite the following paper:

J. P. Ebenezer, Z. Shang, Y. Wu, H. Wei and A. C. Bovik, "No-Reference Video Quality Assessment Using Space-Time Chips," 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP), 2020, pp. 1-6, doi: 10.1109/MMSP48831.2020.9287151.

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