huuthientran/HumanRef

Grounding training data — raw TSV bundle

This repository currently contains HumanRef training data only, repackaged into the indexed TSV storage layout used by Rex-Omni-Finetune-ToyData. It is a derived storage export, not an official HumanRef release.

Dataset	Split	Query rows	Positive	Rejection
HumanRef	train	45,408	37,057	8,351

There are 86,937 selected target boxes. Images are stored as 45,408 source records; repeated images are retained. A prior decoded-image audit found 14,723 unique RGB images. This release contains no validation or test split.

Download and load

Download repository files with huggingface_hub.snapshot_download or the Hub CLI, then use the included plain Python reader. This is an indexed TSV bundle, not a Parquet dataset or a Hugging Face datasets.load_dataset loading script.

pip install huggingface_hub 'Pillow>=10,<13'

import sys
from huggingface_hub import snapshot_download

root = snapshot_download(
    repo_id="huuthientran/HumanRef",
    repo_type="dataset",
    allow_patterns=["humanref/*", "loader.py", "requirements.txt", "benchmarks.json"],
)
sys.path.insert(0, root)
from loader import RawTSVDataset

data = RawTSVDataset(f"{root}/humanref")
raw = data[0]                     # original image_bytes + annotation dictionary
sample = data.decode(raw)         # RGB image; no EXIF auto-rotation
boxes = sample["annotation"]["boxes"]
positive = RawTSVDataset(f"{root}/humanref", positive_only=True)

The loader requires only Pillow. Pin revision in snapshot_download to a repository commit for reproducible experiments. Data files total about 11 GiB.

Files and format

README.md
loader.py
requirements.txt
benchmarks.json
humanref/
  train.images.tsv
  train.images.tsv.lineidx
  train.annotations.tsv
  train.annotations.tsv.lineidx
  train.positive.annotations.tsv.lineidx
  images.jsonl
  manifest.json
  validation.json
  SOURCE_LICENSE

Image rows are image_byte_offset<TAB>base64_original_image_bytes. Annotation rows are image_byte_offset<TAB>annotation_JSON. Each .lineidx stores byte offsets, not row numbers. The positive index selects positive annotation rows without rewriting the base data. images.jsonl records image checksums and dimensions; manifest.json records file checksums and source provenance. validation.json reports validation performed before publication.

For positive queries, boxes contains selected targets:

{"bbox": [10, 20, 100, 200], "phrase": "the person on the left"}

For rejection queries, it contains a null box:

{"bbox": null, "phrase": "an unmatched description"}

Boxes are absolute pixel xyxy. Source region_map indices select candidates from original pixel-xywh gt_boxes; only selected candidates become targets. Every query retains the complete original source_annotation, including candidate boxes, region mapping, and source reasoning text, together with source subset and offset provenance. Source reasoning is provenance, not an inference prompt or a direct-box answer. Separate copies of the original annotation TSVs are omitted because their annotations are already embedded in every exported query.

Image bytes and original annotations are preserved. No resizing, re-encoding, EXIF transpose, clipping, normalization, quantization, filtering, or deduplication is applied. Qwen pixel/normalized formatting and Rex coordinate-token formatting belong in the experiment's runtime adapter. For a compatible grounding reader, configure the box format as xyxy.

Scope and quality

All image-byte checksums, file checksums, byte offsets, selected-target mappings, and positive/rejection counts passed validation. Loader samples were decoded; full exports were checked by image checksums and headers, not a second exhaustive raster decode.

This is raw training storage. Known duplicate queries, conflicting targets, and boxes extending beyond image boundaries remain unchanged. Select a training policy explicitly; do not silently clip or treat candidate boxes as targets. The manifest's ready_for_training: false indicates that experiment-specific selection and model formatting are still required, not a failed storage check.

Source and license

Source: IDEA-Research/HumanRef-CoT-45k, revision 9e1afd27358d774f626a78992c7b716fa403da54. Both humanref_cot and humanref_cot_rejection are included in source order. The four source TSV checksums matched the audited source revision.

The upstream IDEA License 1.0 is included unchanged; it grants use for non-commercial research and requires a separate license for commercial use. Original attribution: "T is licensed under the IDEA License 1.0, Copyright (c) IDEA. All Rights Reserved."