metadata
license: apache-2.0
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: id
dtype: int32
- name: image
dtype: image
- name: sensor_type
dtype: string
- name: question_type
dtype: string
- name: question
dtype: string
- name: question_query
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 1455392605
num_examples: 6248
download_size: 903353168
dataset_size: 1455392605
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
SPARK (multi-vision Sensor Perception And Reasoning benchmarK)
SPARK can reduce the fundamental multi-vision sensor information gap between images and multi-vision sensors. We generated 6,248 vision-language test samples automatically to investigate multi-vision sensory perception and multi-vision sensory reasoning on physical sensor knowledge proficiency across different formats, covering different types of sensor-related questions.
Dataset Details
Uses
Direct Use
Source Data
Data Collection and Processing
These instructions are built from five public datasets: MS-COCO, M3FD, Dog&People, RGB-D scene dataset, and UNIFESP X-ray Body Part Classifier Competition dataset.
Citation
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