roboturk
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Cloth folding, bowl stacking
Split |
Examples |
'test' |
199 |
'train' |
1,796 |
FeaturesDict({
'steps': Dataset({
'action': FeaturesDict({
'gripper_closedness_action': Tensor(shape=(1,), dtype=float32),
'rotation_delta': Tensor(shape=(3,), dtype=float32),
'terminate_episode': float32,
'world_vector': Tensor(shape=(3,), dtype=float32),
}),
'is_first': bool,
'is_last': bool,
'is_terminal': bool,
'observation': FeaturesDict({
'front_rgb': Image(shape=(480, 640, 3), dtype=uint8),
'natural_language_embedding': Tensor(shape=(512,), dtype=float32),
'natural_language_instruction': string,
}),
'reward': Scalar(shape=(), dtype=float32),
}),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
steps |
Dataset |
|
|
|
steps/action |
FeaturesDict |
|
|
|
steps/action/gripper_closedness_action |
Tensor |
(1,) |
float32 |
|
steps/action/rotation_delta |
Tensor |
(3,) |
float32 |
|
steps/action/terminate_episode |
Tensor |
|
float32 |
|
steps/action/world_vector |
Tensor |
(3,) |
float32 |
|
steps/is_first |
Tensor |
|
bool |
|
steps/is_last |
Tensor |
|
bool |
|
steps/is_terminal |
Tensor |
|
bool |
|
steps/observation |
FeaturesDict |
|
|
|
steps/observation/front_rgb |
Image |
(480, 640, 3) |
uint8 |
|
steps/observation/natural_language_embedding |
Tensor |
(512,) |
float32 |
|
steps/observation/natural_language_instruction |
Tensor |
|
string |
|
steps/reward |
Scalar |
|
float32 |
|
@inproceedings{mandlekar2019scaling,
title={Scaling robot supervision to hundreds of hours with roboturk: Robotic manipulation dataset through human reasoning and dexterity},
author={Mandlekar, Ajay and Booher, Jonathan and Spero, Max and Tung, Albert and Gupta, Anchit and Zhu, Yuke and Garg, Animesh and Savarese, Silvio and Fei-Fei, Li},
booktitle={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={1048--1055},
year={2019},
organization={IEEE}
}
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Last updated 2024-12-11 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-12-11 UTC."],[],[],null,["# roboturk\n\n\u003cbr /\u003e\n\n- **Description**:\n\nCloth folding, bowl stacking\n\n- **Homepage** :\n \u003chttps://roboturk.stanford.edu/dataset_real.html\u003e\n\n- **Source code** :\n [`tfds.robotics.rtx.Roboturk`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/robotics/rtx/rtx.py)\n\n- **Versions**:\n\n - **`0.1.0`** (default): Initial release.\n- **Download size** : `Unknown size`\n\n- **Dataset size** : `45.39 GiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'test'` | 199 |\n| `'train'` | 1,796 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'steps': Dataset({\n 'action': FeaturesDict({\n 'gripper_closedness_action': Tensor(shape=(1,), dtype=float32),\n 'rotation_delta': Tensor(shape=(3,), dtype=float32),\n 'terminate_episode': float32,\n 'world_vector': Tensor(shape=(3,), dtype=float32),\n }),\n 'is_first': bool,\n 'is_last': bool,\n 'is_terminal': bool,\n 'observation': FeaturesDict({\n 'front_rgb': Image(shape=(480, 640, 3), dtype=uint8),\n 'natural_language_embedding': Tensor(shape=(512,), dtype=float32),\n 'natural_language_instruction': string,\n }),\n 'reward': Scalar(shape=(), dtype=float32),\n }),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|------------------------------------------------|--------------|---------------|---------|-------------|\n| | FeaturesDict | | | |\n| steps | Dataset | | | |\n| steps/action | FeaturesDict | | | |\n| steps/action/gripper_closedness_action | Tensor | (1,) | float32 | |\n| steps/action/rotation_delta | Tensor | (3,) | float32 | |\n| steps/action/terminate_episode | Tensor | | float32 | |\n| steps/action/world_vector | Tensor | (3,) | float32 | |\n| steps/is_first | Tensor | | bool | |\n| steps/is_last | Tensor | | bool | |\n| steps/is_terminal | Tensor | | bool | |\n| steps/observation | FeaturesDict | | | |\n| steps/observation/front_rgb | Image | (480, 640, 3) | uint8 | |\n| steps/observation/natural_language_embedding | Tensor | (512,) | float32 | |\n| steps/observation/natural_language_instruction | Tensor | | string | |\n| steps/reward | Scalar | | float32 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `None`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\n- **Citation**:\n\n @inproceedings{mandlekar2019scaling,\n title={Scaling robot supervision to hundreds of hours with roboturk: Robotic manipulation dataset through human reasoning and dexterity},\n author={Mandlekar, Ajay and Booher, Jonathan and Spero, Max and Tung, Albert and Gupta, Anchit and Zhu, Yuke and Garg, Animesh and Savarese, Silvio and Fei-Fei, Li},\n booktitle={2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},\n pages={1048--1055},\n year={2019},\n organization={IEEE}\n }"]]