| Name | Version | Summary | date |
| psnr-hvsm |
0.2.4 |
Accelerated implementations of the PSNR-HVS, PSNR-HVS-M, PSNR-HA and PSNR-HMA image metrics for NumPy and PyTorch |
2024-07-26 10:42:15 |
| m2metricforge |
0.0.4 |
Library for generating validation dataset and evaluation metrics |
2024-06-11 20:51:23 |
| bert-score-flex-plot-example |
0.3.16 |
An unofficial fork of PyTorch implementation of BERT score |
2024-03-08 23:26:56 |
| CEScore |
0.0.1 |
Set of an automatic metrics to evaluate the simplicity, meaning preservation, and grammaticality of a simplified text by comparing it with the original complex text as a reference. |
2023-12-05 05:12:31 |
| scale-score |
0.1.0 |
Implementation of SCALE metric and ScreenEval |
2023-11-29 20:01:25 |
| DeepDC-PyTorch |
0.2 |
DeepDC: Deep Distance Correlation as a Perceptual Image Quality Evaluator |
2023-11-24 13:32:01 |
| sewar |
0.4.6 |
All image quality metrics you need in one package. |
2023-07-30 17:08:23 |
| rquge |
0.3 |
PyTorch implementation of RQUGE score |
2023-06-15 14:53:01 |
| code-bert-score |
0.4.1 |
PyTorch implementation of Code BERT score |
2023-06-06 18:02:48 |
| DTCO |
0.1.3 |
DTCO Utility |
2023-05-12 11:37:34 |
| statistical-distance |
0.9.1 |
Distance measures to compare two probability density functions. |
2023-03-19 12:15:07 |
| bert-score |
0.3.13 |
PyTorch implementation of BERT score |
2023-02-20 21:07:29 |
| vision-evaluation |
0.2.13 |
Evaluation metric codes for various vision tasks. |
2023-02-08 23:07:12 |
| rexmex |
0.1.3 |
A General Purpose Recommender Metrics Library for Fair Evaluation. |
2023-01-10 09:51:08 |
| libertymetric |
0.1.4 |
Liberty Metric Utility |
2022-12-09 10:32:03 |
| seqmetric |
0.1.2 |
seq is a seq eval package |
2022-11-25 09:26:07 |
| DISTS-pytorch |
0.1 |
Deep Image Structure and Texture Similarity (DISTS) Metric |
2020-04-17 00:40:40 |
| StringDist |
1.0.9 |
This package provides the stringdist module, which includes several functions for calculating string distances. Under the hood, a C extension module is preferentially used for optimal performance, with an automatic fallback to a Python implementation. |
2017-05-11 07:54:54 |