--- 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: 33800694.0 num_examples: 347 download_size: 33755238 dataset_size: 33800694.0 - 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: 31270976.0 num_examples: 345 download_size: 31240949 dataset_size: 31270976.0 - 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: 22656597.0 num_examples: 674 download_size: 22591665 dataset_size: 22656597.0 - 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: 16315782.0 num_examples: 185 download_size: 16313529 dataset_size: 16315782.0 - 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: 12072018.0 num_examples: 194 download_size: 11900512 dataset_size: 12072018.0 - 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: 12606317.0 num_examples: 92 download_size: 12606757 dataset_size: 12606317.0 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](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ## 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