--- 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

TaskMeAnything-v1-imageqa-random dataset

🌐 Website | 📑 Paper | 🤗 Huggingface | 💻 Interface

If you like our project, please give us a star ⭐ on GitHub for latest update.
## 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: jieyuz2@cs.washington.edu ## 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} } ```