| # CVQA for VLMEvalKit | |
| - [Original dataset:](https://huggingface.co/datasets/afaji/cvqa) ported to [VLMEvalKit](https://github.com/open-compass/VLMEvalKit) | |
| - From the original authors: | |
| > CVQA is a culturally diverse multilingual VQA benchmark consisting of over 10,000 questions from 39 country-language pairs. The questions in CVQA are written in both the native languages and English, and are categorized into 10 diverse categories. | |
| ``` | |
| {'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2048x1536 at 0x7C3E0EBEEE00>, | |
| 'ID': '5919991144272485961_0', | |
| 'Subset': "('Japanese', 'Japan')", | |
| 'Question': '写真に写っているキャラクターの名前は？ ', | |
| 'Translated Question': 'What is the name of the object in the picture? ', | |
| 'Options': ['コスモ星丸', 'ミャクミャク', ' フリービー ', 'ハイバオ'], | |
| 'Translated Options': ['Cosmo Hoshimaru','MYAKU-MYAKU','Freebie ','Haibao'], | |
| 'Label': -1, | |
| 'Category': 'Objects / materials / clothing', | |
| 'Image Type': 'Self', | |
| 'Image Source': 'Self-open', | |
| 'License': 'CC BY-SA' | |
| } | |
| ``` | |
| - To support VLMEvalKit, two TSV files were created to represent the two versions of CVQA: | |
| 1. The localised **(LOC)** version. The questions and answer options are in the subset's original native language. For evaluating with multilingual LLMs. | |
| 2. The english **(ENG)** version. Questions and answers are asked in translated English, although the topics of the question involve cultures other than English. For evaluating on LLMs trained primarily on English. | |
| - TSV row data columns for **LOC** and **ENG** [VLMEvalKit](https://github.com/timothycdc/VLMEvalKit/blob/main/docs/en/Development.md): | |
| - index (int, based on dataset order. Does not follow CVQA ids since they are of type str) | |
| - image (base64) | |
| - question | |
| - A option | |
| - B option | |
| - C option | |
| - D option | |
| - l2-category (`Subset`) | |
| - split (always called `test`) | |
| ## Info | |
| - Proposed method of evaluation: | |
| - Prompt the model to answer only with the correct option letter (one of `[A,B,C,D]`) | |
| - Use regex or string search to locate the correct letter | |
| - Alternatively, use LLM-as-a-judge to identify the correct answer letter. Although, this is a bit of an overkill. | |
| - The original CVQA dataset numbers the options as `[0,1,2,3]`, however this has been changed to`[A,B,C,D]` to follow the VLMEvalKit standard. This shouldn't have much effect on performance. |