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---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: question
    dtype: string
  - name: options
    list: string
  - name: answer
    dtype: string
  - name: task_plan
    dtype: string
  - name: image
    dtype: image
  splits:
  - name: random_3d_how_many
    num_bytes: 436215710.0
    num_examples: 300
  - name: random_3d_what
    num_bytes: 434742201.0
    num_examples: 300
  - name: random_3d_where
    num_bytes: 439317620.0
    num_examples: 300
  - name: random_3d_what_attribute
    num_bytes: 444189904.0
    num_examples: 300
  - name: random_3d_where_attribute
    num_bytes: 440677951.0
    num_examples: 300
  - name: random_3d_what_distance
    num_bytes: 432425889.0
    num_examples: 300
  - name: random_3d_where_distance
    num_bytes: 429200001.0
    num_examples: 300
  - name: random_3d_what_attribute_distance
    num_bytes: 427282309.0
    num_examples: 300
  - name: random_3d_what_size
    num_bytes: 442839308.0
    num_examples: 300
  - name: random_3d_where_size
    num_bytes: 436236948.0
    num_examples: 300
  - name: random_3d_what_attribute_size
    num_bytes: 438653169.0
    num_examples: 300
  - name: random_2d_how_many
    num_bytes: 19675524.0
    num_examples: 300
  - name: random_2d_what
    num_bytes: 20867143.0
    num_examples: 300
  - name: random_2d_where
    num_bytes: 20328953.0
    num_examples: 300
  - name: random_2d_what_attribute
    num_bytes: 20040624.0
    num_examples: 300
  - name: random_2d_where_attribute
    num_bytes: 22044710.0
    num_examples: 300
  - name: random_sg_what_object
    num_bytes: 13414061.0
    num_examples: 300
  - name: random_sg_what_attribute
    num_bytes: 12339318.0
    num_examples: 300
  - name: random_sg_what_relation
    num_bytes: 12630575.0
    num_examples: 300
  download_size: 4916677872
  dataset_size: 4943121918.0
configs:
- config_name: default
  data_files:
  - split: random_3d_how_many
    path: data/random_3d_how_many-*
  - split: random_3d_what
    path: data/random_3d_what-*
  - split: random_3d_where
    path: data/random_3d_where-*
  - split: random_3d_what_attribute
    path: data/random_3d_what_attribute-*
  - split: random_3d_where_attribute
    path: data/random_3d_where_attribute-*
  - split: random_3d_what_distance
    path: data/random_3d_what_distance-*
  - split: random_3d_where_distance
    path: data/random_3d_where_distance-*
  - split: random_3d_what_attribute_distance
    path: data/random_3d_what_attribute_distance-*
  - split: random_3d_what_size
    path: data/random_3d_what_size-*
  - split: random_3d_where_size
    path: data/random_3d_where_size-*
  - split: random_3d_what_attribute_size
    path: data/random_3d_what_attribute_size-*
  - split: random_2d_how_many
    path: data/random_2d_how_many-*
  - split: random_2d_what
    path: data/random_2d_what-*
  - split: random_2d_where
    path: data/random_2d_where-*
  - split: random_2d_what_attribute
    path: data/random_2d_what_attribute-*
  - split: random_2d_where_attribute
    path: data/random_2d_where_attribute-*
  - split: random_sg_what_object
    path: data/random_sg_what_object-*
  - split: random_sg_what_attribute
    path: data/random_sg_what_attribute-*
  - split: random_sg_what_relation
    path: data/random_sg_what_relation-*
---

# Dataset Card for TaskMeAnything-v1-imageqa-random
<h2 align="center"> TaskMeAnything-v1-imageqa-random dataset</h2>

<h2 align="center"> <a href="https://www.task-me-anything.org/">🌐 Website</a> | <a href="https://arxiv.org/abs/2406.11775">πŸ“‘ Paper</a> | <a href="https://huggingface.co/collections/jieyuz2/taskmeanything-664ebf028ab2524c0380526a">πŸ€— Huggingface</a> | <a href="https://huggingface.co/spaces/zixianma/TaskMeAnything-UI">πŸ’» Interface</a></h2>
    
<h5 align="center"> If you like our project, please give us a star ⭐ on GitHub for latest update.  </h2>

## TaskMeAnything-v1-Random
[TaskMeAnything-v1-imageqa-random](https://huggingface.co/datasets/weikaih/TaskMeAnything-v1-imageqa-random) is a dataset which using
randomly sampled questions from TaskMeAnything-v1, including 5,700 ImageQA questions. The dataset contains 19 splits, while each splits contains 300 questions from a specific task generator in TaskMeAnything-v1. For each row of dataset, it includes: image, question, options, answer and its corresponding task plan.

## Load TaskMeAnything-v1-Random ImageQA Dataset
```
import datasets

dataset_name = 'weikaih/TaskMeAnything-v1-imageqa-random'
dataset = datasets.load_dataset(dataset_name, split = TASK_GENERATOR_SPLIT)
```
where `TASK_GENERATOR_SPLIT` is one of the task generators, eg, `random_2d_how_many`.

## Evaluation Results

### Overall
![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cb0dcc4913057ac82a7a31/9x9dloN9fKRBj-VUJijXB.png)

### Breakdown performance on each task types
![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cb0dcc4913057ac82a7a31/8gq7G9Ky228eooi9Mt4ep.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cb0dcc4913057ac82a7a31/ux-4o12LCDdyqGSLFl2CX.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cb0dcc4913057ac82a7a31/oVZlgtlqDVR_oQj32ZeEj.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65cb0dcc4913057ac82a7a31/UEbtq1FIPfvvoYdk6UIf0.png)

## Out-of-Scope Use
This dataset should not be used for training models.


## Disclaimers
**TaskMeAnything** and its associated resources are provided for research and educational purposes only. 
The authors and contributors make no warranties regarding the accuracy or reliability of the data and software. 
Users are responsible for ensuring their use complies with applicable laws and regulations. 
The project is not liable for any damages or losses resulting from the use of these resources.

## Contact

- Jieyu Zhang: [email protected]

## Citation
**BibTeX:**
```bibtex
@article{zhang2024task,
  title={Task Me Anything},
  author={Zhang, Jieyu and Huang, Weikai and Ma, Zixian and Michel, Oscar and He, Dong and Gupta, Tanmay and Ma, Wei-Chiu and Farhadi, Ali and Kembhavi, Aniruddha and Krishna, Ranjay},
  journal={arXiv preprint arXiv:2406.11775},
  year={2024}
}
```