---
tags:
- robo-vqa
- embodied-ai
- visual-question-answering
- video-understanding
- physbrain-evalkit
---

# RoboVQA 16-Frame Evaluation Dataset

This dataset package provides the 16-frame RoboVQA evaluation data used by the [PhysBrainEvalKit](https://github.com/DeepCybo-PhysAI/PhysBrainEvalKit) project. It is intended for reproducible evaluation of vision-language models on the RoboVQA benchmark with the PhysBrainEvalKit `eval_robovqa.py` adapter.

## Contents

- `qa.jsonl`: 1,921 evaluation examples. Each row contains the question, answer metadata, and 16 ordered frame paths.
- `clips.jsonl`: clip-level metadata used to identify the source video clips.
- `metadata.json`: dataset construction and sample-count metadata.
- `frames.tar`: 21,360 JPEG frames from 1,335 unique clips. The archive stores the files under the `frames/` prefix.

The evaluation protocol expects exactly 16 time-ordered frames for every QA example. Frame paths in `qa.jsonl` are resolved relative to this dataset directory or to members in `frames.tar`.

## Use with PhysBrainEvalKit

Set the dataset root to the directory containing `qa.jsonl` and `frames.tar`:

```bash
export ROBOVQA_DATA_ROOT=/path/to/RoboVQA-16frames
```

Then run the RoboVQA benchmark from the PhysBrainEvalKit repository:

```bash
python eval_robovqa.py \
  --model_path /path/to/qwen3_vl_model \
  --model_name qwen3-vl \
  --backbone qwen3 \
  --backend hf \
  --data_root "$ROBOVQA_DATA_ROOT" \
  --expected_num_frames 16
```

The PhysBrainEvalKit loader reads images from `frames.tar` on demand. Manual extraction is not required. Keeping the archive intact avoids creating thousands of separate image files.

## File format

`qa.jsonl` is newline-delimited JSON. The loader requires a non-empty `frame_paths` list in every row and validates that it contains 16 entries. Relative frame paths must match the corresponding members in `frames.tar`.

## Provenance and licensing

This package is a prepared evaluation layout for PhysBrainEvalKit. RoboVQA content and any underlying media remain subject to the terms of the original RoboVQA dataset and its source datasets. Review the upstream dataset license and citation requirements before redistribution or publication.