license: mit | |
# Visual Haystacks Dataset Card | |
## Dataset details | |
1. Dataset type: Visual Haystacks (VHs) is a benchmark dataset specifically designed to evaluate the Large Multimodal Model's (LMM's) capability to handle long-context visual information. It can also be viewed as the first visual-centric Needle-In-A-Haystack (NIAH) benchmark dataset. Please also download COCO-2017's training set validation set. | |
2. Data Preparation and Benchmarking | |
- Download the VQA questions: | |
``` | |
huggingface-cli download --repo-type dataset tsunghanwu/visual_haystacks --local-dir dataset/VHs_qa | |
``` | |
- Download the COCO 2017 dataset and organize it as follows, with the default root directory ./dataset/coco: | |
``` | |
dataset/ | |
βββ coco | |
β βββ annotations | |
β βββ test2017 | |
β βββ val2017 | |
βββ VHs_qa | |
βββ VHs_full | |
β βββ multi_needle | |
β βββ single_needle | |
βββ VHs_small | |
βββ multi_needle | |
βββ single_needle | |
``` | |
- Follow the instructions in https://github.com/visual-haystacks/vhs_benchmark to run the evaluation | |
3. Please check out our [project page](https://visual-haystacks.github.io) for more information. You can also send questions or comments about the model to [our github repo](https://github.com/visual-haystacks/vhs_benchmark/issues) | |
## Intended use | |
Primary intended uses: The primary use of VHs is research on large multimodal models and chatbots. | |
Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence. |