Datasets:

yunus-emre
/

uav-drone-reasoning-vqa

language: en
license: apache-2.0
task_categories:
  - visual-question-answering
  - object-detection
tags:
  - uav
  - drone
  - reasoning
  - vqa
  - chain-of-thought
  - qwen-vl
  - counter-uas
configs:
  - config_name: v2
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*

UAV Drone Reasoning VQA Dataset v2

Multimodal VQA dataset for counter-UAS training with rich chain-of-thought reasoning.

v2 Improvements

Negative and hard-negative samples (birds/aircraft distractors)
Category-labeled QA pairs
Richer multi-sentence thinking traces
Qwen-VL chat messages format with `` blocks
Stratified train/validation/test splits
Duplicate-question downweighting via dup_weight

Stats

Records: 14,909
QA pairs: 98,837
Unique questions: 14,590
Sources: {'kaggle_v1': 9909, 'negative': 2500, 'hard_negative': 2500}

Fields

Field	Description
`image`	PIL-ready surveillance image
`messages`	Qwen chat JSON (user question + assistant thinking/answer)
`ground_truth`	Pixel xyxy boxes + class
`ground_truth_norm`	0-1000 normalized boxes
`categories`	QA category labels
`dup_weight`	Sampling weight for deduplicated training
`source`	kaggle_v1 / negative / hard_negative

Usage

from datasets import load_dataset
import json

ds = load_dataset("yunus-emre/uav-drone-reasoning-vqa", "v2")
row = ds["train"][0]
messages = json.loads(row["messages"])