visual_haystacks_v0 / README.md
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---
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/
β”œβ”€β”€ coco
β”‚ β”œβ”€β”€ annotations
β”‚ β”œβ”€β”€ test2017
β”‚ └── val2017
└── VHs_qa
β”œβ”€β”€ VHs_full
β”‚ β”œβ”€β”€ multi_needle
β”‚ └── single_needle
└── VHs_small
β”œβ”€β”€ multi_needle
└── 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.