metadata
license: mit
task_categories:
- image-segmentation
- image-classification
- object-detection
pretty_name: Semantic segmenation and pose estimation from RGB-D
dataset_info:
features:
- name: rgb
dtype: image
- name: depth
dtype: image
- name: mask
dtype: image
- name: meta
list:
- name: colors
sequence: float64
- name: file
dtype: string
- name: id
dtype: int64
- name: model
dtype: string
- name: numberOfColors
dtype: int64
- name: orientation
sequence: float64
- name: position
sequence: float64
- name: positionOnImage
sequence: int64
- name: size
sequence: float64
- name: sizeOnImage
sequence: int64
splits:
- name: train
num_bytes: 3340733260.96
num_examples: 1106
download_size: 3319212411
dataset_size: 3340733260.96
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
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. Each instance contains a mask image as well meta data containing labels, position, and size of each object.