robo_net_raw / features.json
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{
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
"featuresDict": {
"features": {
"steps": {
"pythonClassName": "tensorflow_datasets.core.features.dataset_feature.Dataset",
"sequence": {
"feature": {
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
"featuresDict": {
"features": {
"observation": {
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
"featuresDict": {
"features": {
"image": {
"pythonClassName": "tensorflow_datasets.core.features.image_feature.Image",
"image": {
"shape": {
"dimensions": [
"240",
"320",
"3"
]
},
"dtype": "uint8",
"encodingFormat": "jpeg"
},
"description": "Main camera RGB observation."
},
"image1": {
"pythonClassName": "tensorflow_datasets.core.features.image_feature.Image",
"image": {
"shape": {
"dimensions": [
"240",
"320",
"3"
]
},
"dtype": "uint8",
"encodingFormat": "jpeg"
},
"description": "Main camera RGB observation."
},
"image2": {
"pythonClassName": "tensorflow_datasets.core.features.image_feature.Image",
"image": {
"shape": {
"dimensions": [
"240",
"320",
"3"
]
},
"dtype": "uint8",
"encodingFormat": "jpeg"
},
"description": "Main camera RGB observation."
},
"state": {
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
"tensor": {
"shape": {
"dimensions": [
"5"
]
},
"dtype": "float32",
"encoding": "none"
},
"description": "Robot state, consists of eef position, wristorientation, and gripper state[e_x, e_y, e_z, theta, gripper]."
}
}
}
},
"reward": {
"pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
"tensor": {
"shape": {},
"dtype": "float32",
"encoding": "none"
},
"description": "Reward if provided, 0 for all random data."
},
"is_first": {
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
"tensor": {
"shape": {},
"dtype": "bool",
"encoding": "none"
}
},
"is_terminal": {
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
"tensor": {
"shape": {},
"dtype": "bool",
"encoding": "none"
}
},
"action": {
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
"tensor": {
"shape": {
"dimensions": [
"5"
]
},
"dtype": "float32",
"encoding": "none"
},
"description": "Robot action, consists of [3x eef delta, 1x wrist rotation, 1x gripper width target]."
},
"discount": {
"pythonClassName": "tensorflow_datasets.core.features.scalar.Scalar",
"tensor": {
"shape": {},
"dtype": "float32",
"encoding": "none"
},
"description": "Discount if provided, default to 1."
},
"language_embedding": {
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
"tensor": {
"shape": {
"dimensions": [
"512"
]
},
"dtype": "float32",
"encoding": "none"
},
"description": "Kona language embedding. See https://tfhub.dev/google/universal-sentence-encoder-large/5"
},
"is_last": {
"pythonClassName": "tensorflow_datasets.core.features.tensor_feature.Tensor",
"tensor": {
"shape": {},
"dtype": "bool",
"encoding": "none"
}
},
"language_instruction": {
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
"text": {},
"description": "Language Instruction."
}
}
}
},
"length": "-1"
}
},
"episode_metadata": {
"pythonClassName": "tensorflow_datasets.core.features.features_dict.FeaturesDict",
"featuresDict": {
"features": {
"file_path": {
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
"text": {},
"description": "Path to the original data file."
},
"robot": {
"pythonClassName": "tensorflow_datasets.core.features.text_feature.Text",
"text": {},
"description": "Robot model used during data collection."
}
}
}
}
}
}
}