Name | Modified | Size | Downloads / Week |
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Parent folder | |||
torchmetrics-1.8.0.tar.gz | 2025-07-23 | 578.9 kB | |
torchmetrics-1.8.0-py3-none-any.whl | 2025-07-23 | 981.9 kB | |
First video and vertex metrics source code.tar.gz | 2025-07-23 | 1.0 MB | |
First video and vertex metrics source code.zip | 2025-07-23 | 1.8 MB | |
README.md | 2025-07-23 | 3.3 kB | |
Totals: 5 Items | 4.4 MB | 2 |
The upcoming TorchMetrics v1.8.0 release introduces three flagship metrics, each designed to address critical evaluation needs in real-world applications.
Video Multi-Method Assessment Fusion (VMAF) brings a perceptual video-quality score that closely mirrors human judgment, powering streaming services such as Netflix and YouTube to optimize encoding ladders for consistent viewer experiences and enabling video-restoration labs to quantify improvements achieved by denoising and super-resolution algorithms.
Continuous Ranked Probability Score (CRPS) enables comprehensive evaluation of full predictive distributions rather than point estimates; meteorological centers leverage CRPS to benchmark probabilistic precipitation and temperature forecasts, improving public weather alerts, while energy companies apply it to assess uncertainty in load-demand predictions and refine grid management and trading strategies.
Lip Vertex Error (LVE) measures the discrepancy between predicted and ground-truth lip landmarks to quantify audio-visual synchronization. Localization studios use LVE to validate lip-sync accuracy during film dubbing, while AR/VR developers integrate it into avatar pipelines to ensure natural mouth movements in real-time virtual meetings and social experiences.
[1.8.0] - 2025-07-23
Added
- Added
VMAF
metric to new video domain (#2991) - Added
CRPS
in regression domain (#3024) - Added
aggregation_level
argument toDiceScore
(#3018) - Added support for
reduction="none"
toLearnedPerceptualImagePatchSimilarity
(#3053) - Added support single
str
input for functional interface ofbert_score
(#3056) - Enhance:
BERTScore
to evaluate hypotheses against multiple references (#3069) - Added
Lip Vertex Error (LVE)
in multimodal domain (#3090) - Added
antialias
argument toFID
metric (#3177) - Added
mixed
input format to segmentation metrics (#3176)
Changed
- Changed
data_range
argument inPSNR
metric to be a required argument (#3178)
Removed
- Removed
zero_division
argument fromDiceScore
(#3018)
Key Contributors
@nkaenzig, @rittik9, @simonreise, @SkafteNicki
New Contributors
- @lantiga made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3054
- @AlexVerine made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3057
- @ZhiyuanChen made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3059
- @ahmedhshahin made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3101
- @gratus907 made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3103
- @cyyever made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3118
- @Armannas made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3124
- @alifa98 made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3128
- @simonreise made their first contribution in https://github.com/Lightning-AI/torchmetrics/pull/3176
If we forgot someone due to not matching commit email with GitHub account, let us know :]
Full Changelog: https://github.com/Lightning-AI/torchmetrics/compare/v1.7.0...v1.8.0