# VideoSearcher RL Training Data

RL training/validation data for VideoSearcher (video deep-research agent), as used by
`train_video_test_GSPO_HDPO_image.sh`. All paths inside the annotation files are
**relative to this directory**.

## Contents

| File / Dir | Description |
|---|---|
| `train_video_deepresearch_qcap1_plus_0505.json` | Train dataset config (points to the train jsonl) |
| `test_video_deepresearch.json` | Val dataset config (points to the val jsonl) |
| `all_video_deepresearch_qcap1_plus_video_dr_0505_rl.jsonl` | Train annotations, 3285 samples |
| `val_video_deepresearch_data.le20min.jsonl` | Val annotations, 348 samples |
| `videos/<id>/all_frames/frame_*.jpg` | 1fps frames for fvqa videos (2324 videos) |
| `frames_dr0505/<id>/frame_*.jpg` | 1fps frames for video_dr_0505 videos (1124 videos) |

Each jsonl line has an `image` field listing frame paths (relative), e.g.
`videos/fvqa_1002__yUuVs1AMjHk/all_frames/frame_000000.jpg` or
`frames_dr0505/vdr_015_.../frame_000000.jpg`.

Frame index (1fps) is watermarked in the top-left corner of every frame.

## Usage

Unzip all parts into one directory. To train, point the dataset configs' `annotation`
field (or your data root) at this directory, or prepend this directory's absolute path
to the relative paths in the jsonl `image` fields.