Datasets:
Tasks:
Visual Question Answering
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
< 1K
License:
File size: 1,884 Bytes
1a32a03 6dbb636 1a32a03 9015339 1a32a03 9015339 1a32a03 6dbb636 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | ---
license: other
task_categories:
- visual-question-answering
language:
- en
pretty_name: AutoV Attention-Map Training Data
---
# AutoV Attention-Map Training Data
This dataset repository contains the training metadata and derived
attention-map images used by AutoV. It does not contain the original source
images.
## Contents
### Training data
- `metadata/llava_v1_5_mix100k_reward.json`: 100,000 reward-training records.
- `metadata/llava_v1_5_mix100k_filter.json`: the corresponding filtered records.
- `metadata/llava_v1_5_mix1k_*.json`: the 1,000-record development subset.
- `archives/attnmap100K/`: 20 tar archives containing 400,000 attention maps.
- `archives/attnmap1K/`: 4 tar archives containing 4,000 attention maps.
- `SHA256SUMS`: integrity checks for metadata and archives.
### Inference data
- `inference-data/mmvet/`: 800 MMVet attention-map images (200 image names
across CLIP ViT-L/14@336 layers 15, 20, 22, and 23). The directory layout
matches `LLaVA/playground/data/api_eval/mmvet`.
The 100K metadata references 25,000 COCO, 20,000 Visual Genome, 20,000 GQA,
20,000 OCR-VQA, and 15,000 TextVQA source-image paths. Each record has four
derived attention maps from CLIP ViT-L/14@336 layers 15, 20, 22, and 23.
## Restore the original AutoV data layout
Run from the downloaded repository root:
```bash
mkdir -p data/attnmap100K data/attnmap1K
for archive in archives/attnmap100K/*.tar; do
tar -xf "$archive" -C data/attnmap100K
done
for archive in archives/attnmap1K/*.tar; do
tar -xf "$archive" -C data/attnmap1K
done
cp metadata/* data/
sha256sum -c SHA256SUMS
```
## Licensing note
The metadata refers to COCO, Visual Genome, GQA, OCR-VQA, TextVQA, and LLaVA
data. Their original licenses and terms continue to apply. Redistribution of
the derived attention-map images was reviewed against the applicable source
terms before publication.
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