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lmms-lab-eval/repcount

RepCount Full-set metadata for lmms-eval task repcount. Dataset Contents This repository contains metadata/annotations only. Raw video files are not embedded in this repo. QA Format Each row is count-based QA for repetition counting: video / video_id: media reference question: natural-language counting prompt count: integer ground-truth repetition count action_type (optional): action category metadata In lmms-eval, targets are read from count… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-eval/repcount.

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RepCount

Full-set metadata for lmms-eval task repcount.

Dataset Contents

This repository contains metadata/annotations only. Raw video files are not embedded in this repo.

QA Format

Each row is count-based QA for repetition counting:

—video / video_id: media reference
—question: natural-language counting prompt
—count: integer ground-truth repetition count
—action_type (optional): action category metadata

In lmms-eval, targets are read from count first (fallbacks: answer, number, gt_count, label), and scored by mae_norm and obo.

Raw Media Requirement

—Metadata source: https://github.com/sinhasaptarshi/EveryShotCounts (datasets/repcount/*_with_fps.csv)
—Raw video location: official RepCount downloads / YouTube-derived media (not embedded here)
—Expected local media root for evaluation: $REPCOUNT_VIDEO_DIR or $HF_HOME/repcount

Attribution and Relationship

RepCount is introduced in TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting (CVPR 2022, arXiv:2204.01018). Countix is a separate dataset introduced in Counting Out Time (CVPR 2020, arXiv:2006.15418). RepCount and Countix are independent datasets from different research groups.