We also provide two sample datasets including the video files and the properly formatted dataset files in Python. They can be used as sample datasets to train and test custom VMAF models.
We provide a dataset publicly available to the community for training, testing and verification of results purposes. The dataset file is at NFLX_dataset_public.py, and the videos (in YUV420P format) can be downloaded here. Each file name is in the format of {content name}_{expert score}_{height in pixels}_{bitrate in Kbps}.yuv. For example, BirdsInCage_85_720_1050.yuv is an decompressed video from content BirdInCage, with an expert opinion score 85 out of 100, compressed with 720p resolution at 1050 Kbps. Note that the expert opinion score is different from the MOS score offered in NFLX_dataset_public.py, which are from a panel of non-expert subjects.
We also provide an example dataset file containing video file names from VQEG (Video Quality Expert Group) HD3 videos. The dataset file is at VQEGHD3_dataset.py, and the videos are available for downloading from http://www.cdvl.org/. After login, choose 'Advanced Search', select 'VQEG Subjective Tests' in the dataset dropdown, and search for the keyword 'vqeghd3'. This will return a single combined ZIP file of ~84 GB, 'VQEG HDTV Test, vqeghd3' as the individual sequences are no longer available for download. The dataset file includes from src01 to src09 except for src04, which overlaps with the Netflix Public Dataset, and hrc04, hrc07, hrc16, hrc17, hrc18, hrc19, hrc20 and hrc21, which are the most relevant distortion types to adaptive streaming. After downloading the videos, convert them to YUV420P format.