Datasets:
dataset_info:
- config_name: animals
features:
- name: Filename
dtype: string
- name: full_species_name_DE
dtype: string
- name: full_species_name_EN
dtype: string
- name: family_name_DE
dtype: string
- name: family_name_EN
dtype: string
- name: acceptable_generalization
dtype: string
- name: Alias
dtype: string
- name: Remarks
dtype: string
- name: scientific_name
dtype: string
- name: scientific_family_name
dtype: string
- name: common_name_DE
dtype: string
- name: common_name_EN
dtype: string
- name: language
dtype: string
- name: category
dtype: string
- name: subcategory
dtype: string
- name: self_collected
dtype: string
- name: full_path
dtype: string
- name: image
dtype: image
splits:
- name: test
num_bytes: 33800694
num_examples: 347
download_size: 33755238
dataset_size: 33800694
- config_name: cars
features:
- name: Filename
dtype: string
- name: company
dtype: string
- name: model_name
dtype: string
- name: category_EN
dtype: string
- name: category_DE
dtype: string
- name: language
dtype: string
- name: category
dtype: string
- name: self_collected
dtype: string
- name: full_path
dtype: string
- name: image
dtype: image
splits:
- name: test
num_bytes: 31270976
num_examples: 345
download_size: 31240949
dataset_size: 31270976
- config_name: celebrity
features:
- name: Filename
dtype: string
- name: first_name
dtype: string
- name: last_name
dtype: string
- name: alternative_name
dtype: string
- name: name
dtype: string
- name: subcategory
dtype: string
- name: language
dtype: string
- name: category
dtype: string
- name: self_collected
dtype: string
- name: full_path
dtype: string
- name: full_name
dtype: string
- name: image
dtype: image
splits:
- name: test
num_bytes: 22656597
num_examples: 674
download_size: 22591665
dataset_size: 22656597
- config_name: plants
features:
- name: alternative_name_DE
dtype: string
- name: Alias
dtype: string
- name: scientific_name
dtype: string
- name: common_name_EN
dtype: string
- name: common_name_DE
dtype: string
- name: Filename
dtype: string
- name: language
dtype: string
- name: category
dtype: string
- name: self_collected
dtype: string
- name: full_path
dtype: string
- name: image
dtype: image
splits:
- name: test
num_bytes: 16315782
num_examples: 185
download_size: 16313529
dataset_size: 16315782
- config_name: products
features:
- name: Filename
dtype: string
- name: company_name
dtype: string
- name: product_name
dtype: string
- name: language
dtype: string
- name: category
dtype: string
- name: self_collected
dtype: string
- name: full_path
dtype: string
- name: image
dtype: image
splits:
- name: test
num_bytes: 12072018
num_examples: 194
download_size: 11900512
dataset_size: 12072018
- config_name: sights
features:
- name: Filename
dtype: string
- name: name_DE
dtype: string
- name: name_EN
dtype: string
- name: location_name_DE
dtype: string
- name: location_name_EN
dtype: string
- name: language
dtype: string
- name: category
dtype: string
- name: self_collected
dtype: string
- name: full_path
dtype: string
- name: image
dtype: image
splits:
- name: test
num_bytes: 12606317
num_examples: 92
download_size: 12606757
dataset_size: 12606317
configs:
- config_name: animals
data_files:
- split: test
path: animals/full-*
- config_name: cars
data_files:
- split: test
path: cars/full-*
- config_name: celebrity
data_files:
- split: test
path: celebrity/full-*
- config_name: plants
data_files:
- split: test
path: plants/full-*
- config_name: products
data_files:
- split: test
path: products/full-*
- config_name: sights
data_files:
- split: test
path: sights/full-*
task_categories:
- visual-question-answering
language:
- en
- de
tags:
- factual-knowledge
- multi-lingual
- biology
- celebrities
- sights
- cars
- supermarket
- products
- ocr
size_categories:
- n<1K
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
- Curated by: Institute for Information Systems (iisys) of Hof University of Applied Sciences, Germany
- Language(s) (NLP): German (de), English (en)
- License: Images are owned by their creators, the collection of data is distributed under cc-by-nc 4.0 license. The data is provided as-is without any warranty or guarantee of fitness for a particular purpose. Please refer to the license file in the repository for more details.
Dataset Sources
Images are collected from the Internet with a focus on images NOT featured on Wikipedia, because we expected those to be less likely to be part of existing training datasets. Images are filtered and downscaled to be within 400x300 as a minimum (except Celeb1k) and 1280x1024 as a maximum.
Paper : currently under review for a scientific AI conference. Will be published in first half of 2025.
Uses
Should be used to evaluate factual knowledge of Vision Language Models (VLMs) with a focus on image contents from Germany in contrast to internationally well-known image contents from English-speaking countries and others.
Out-of-Scope Use
Commercial use or any use that may lead to commercial gain is not permitted without explicit permission from the copyright holders.
Dataset Structure
The dataset consists of six parquet files, one for each category of images, namely animals, plants, celebrities, sights, cars and products from the supermarket (mainly food). Each file contains images with strong association to Germany and semantically similar counterparts from other countries, especially English-speaking ones. The names of the objects that should be identified from the images are given in English and German language.
Dataset Creation and Curation Rationale
The German-related images are self-collected from various sources in the internet, excluding Wikipedia. Images with English- or international focus are partly self-collected, partly filtered and reused contents from existing datasets like Stanford Cars (https://huggingface.co/datasets/tanganke/stanford_cars), Oxford Flowers (https://huggingface.co/datasets/dpdl-benchmark/oxford_flowers102) and Celeb1k (https://huggingface.co/datasets/tonyassi/celebrity-1000). German names are added by iisys.
Annotation process
Annotation was done manually by using Wikipedia and other online resources for verification of the names and Google image search for visual confirmation of the image names in case of doubt. The focus was on asking for common names as used by everyday people, not specialists in the respective field (e.g., not asking for the scientific name of a plant). For animals and plants some common names are rather coarse and refer to the animal or plant family rather than the species, because we expect most people not to know the exact species name and therefore getting the exact right answer would be less helpful than a litte coarser one. However, we accepted the exact species name in latin as a correct answer if the VLM gave this as an answer, but noted it as a deficit in German language if it could not give the German (or English) common name in addition.
Who are the annotators?
René Peinl and Vincent Tischler, iisys, Hof University of Applied Sciences, Hof, Germany
Bias, Risks, and Limitations
The selection of images was biased towards the background knowledge of the annotators and there is no guarantee that it is objectively representative for the respective categories.
Citation
[coming soon]
BibTeX:
[coming soon]
Dataset Card Authors
René Peinl
Dataset Card Contact
René Peinl