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--- |
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license: mit |
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task_categories: |
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- image-segmentation |
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- image-classification |
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- object-detection |
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pretty_name: Semantic segmenation and pose estimation from RGB-D |
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dataset_info: |
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features: |
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- name: rgb |
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dtype: image |
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- name: depth |
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dtype: image |
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- name: mask |
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dtype: image |
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- name: meta |
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list: |
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- name: colors |
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sequence: float64 |
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- name: file |
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dtype: string |
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- name: id |
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dtype: int64 |
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- name: model |
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dtype: string |
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- name: numberOfColors |
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dtype: int64 |
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- name: orientation |
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sequence: float64 |
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- name: position |
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sequence: float64 |
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- name: positionOnImage |
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sequence: int64 |
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- name: size |
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sequence: float64 |
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- name: sizeOnImage |
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sequence: int64 |
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splits: |
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- name: train |
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num_bytes: 3340733260.96 |
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num_examples: 1106 |
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download_size: 3319212411 |
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dataset_size: 3340733260.96 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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RGB-D dataset for instance segmentation (from RGB or depth) and pose estimation of individual objects. Data has been generated by randomizing bin contents in Webots. |
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Each instance contains a mask image as well meta data containing labels, position, and size of each object. |
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<video src='https://cdn-uploads.huggingface.co/production/uploads/655b1b359d249b4ab388d4a2/l6b76ezxkPi6lG3Fr6_kj.mp4' width=720/> |
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You can create your own data by opening webots_grasp.wbt in the world directory using [Webots](https://www.cyberbotics.com). |
