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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
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num_examples: 300
- name: random_3d_what_attribute_distance
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num_examples: 300
- name: random_3d_what_size
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num_examples: 300
- name: random_3d_where_size
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num_examples: 300
- name: random_3d_what_attribute_size
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num_examples: 300
- name: random_2d_how_many
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num_examples: 300
- name: random_2d_what
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num_examples: 300
- name: random_2d_where
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num_examples: 300
- name: random_2d_what_attribute
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num_examples: 300
- name: random_2d_where_attribute
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num_examples: 300
- name: random_sg_what_object
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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
<h5 align="center">
<!-- [[**📖 Paper**]() ** | [**🤗 TaskMeAnything-v1-Random**]() | [**🤗 TaskMeAnything-DB**]() | [**🤗 TaskMeAnything-UI**]() -->
</h5>
## TaskMeAnything-v1-Random
[TaskMeAnything-v1-imageqa-random](https://huggingface.co/datasets/weikaih/TaskMeAnything-v1-imageqa-random) is a dataset which 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`.
## 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
``` |