Fusion Dataset Structure¶
TensorBay also defines a uniform fusion dataset format. This topic explains the related concepts. The TensorBay fusion dataset format looks like:
fusion dataset
├── notes
├── catalog
│ ├── subcatalog
│ ├── subcatalog
│ └── ...
├── fusion segment
│ ├── sensors
│ │ ├── sensor
│ │ ├── sensor
│ │ └── ...
│ ├── frame
│ │ ├── data
│ │ └── ...
│ ├── frame
│ │ ├── data
│ │ └── ...
│ └── ...
├── fusion segment
└── ...
fusion dataset¶
Fusion dataset is the topmost concept in TensorBay format. Each fusion dataset includes a catalog and a certain number of fusion segments.
The corresponding class of fusion dataset is FusionDataset
.
notes¶
The notes of the fusion dataset is the same as the notes (ref) of the dataset.
catalog & subcatalog in fusion dataset¶
The catalog of the fusion dataset is the same as the catalog (ref) of the dataset.
fusion segment¶
There may be several parts in a fusion dataset. In TensorBay format, each part of the fusion dataset is stored in one fusion segment. Each fusion segment contains a certain number of frames and multiple sensors, from which the data inside the fusion segment are collected.
The corresponding class of fusion segment is FusionSegment
.
sensor¶
Sensor represents the device that collects the data inside the fusion segment. Currently, TensorBay supports four sensor types.(Table. 2)
Supported Sensors |
Corresponding Data Type |
---|---|
image |
|
image |
|
point cloud |
|
point cloud |
The corresponding class of sensor is Sensor
.
frame¶
Frame is the structural level next to the fusion segment. Each frame contains multiple data collected from different sensors at the same time.
The corresponding class of frame is Frame
.
data in fusion dataset¶
Each data inside a frame corresponds to a sensor. And the data of the fusion dataset is the same as the data (ref) of the dataset.