jakubkrapiec/crf-vmaf-training-data
CRF <-> VMAF training data Training datasets behind Alice-1 - a LightGBM model that predicts the CRF value needed to hit a target VMAF score for a given video segment, codec and resolution. Contents File Rows Description training_table.parquet 1,762,232 Main table. Feature aggregates -> CRF for a target VMAF, per codec/resolution. probe_data.parquet 52,316 Probe-encode data. Two 2s probe encodes per (segment, codec, resolution) cell with measured VMAF… See the full description on the dataset page: https://huggingface.co/datasets/jakubkrapiec/crf-vmaf-training-data.
CRF <-> VMAF training data
Training datasets behind Alice-1 - a LightGBM model that predicts the CRF value needed to hit a target VMAF score for a given video segment, codec and resolution.
Contents
Schema: training_table
One row = (video segment codec target resolution * target VMAF) -> the CRF that achieves that VMAF.
Schema: probe_data
One row = (segment codec resolution) with two cheap probe encodes.
Sources
~40,861 unique (segment, codec, resolution) cells from ~9,000 source clips: Blender Open Movies, Internet Archive public-domain films, NASA SVS, Wikimedia Commons, Pexels/Pixabay/Coverr/Mixkit stock, Xiph.org test media, YouTube CC. All sources are openly licensed.
Citation
If you use this dataset, please link the repo.
License
CC0-1.0 (public domain dedication). Feature aggregates and measurements computed by the authors from openly licensed sources; no video content is included.
