SA-Gate is a neural network that is used for indoor segmentation. The input is a pair of an RGB image and an HHA map generated with the depth map. The output is a heat map where each pixel is predicted with a semantic category, like chair, bed, and other objects typically found indoors.
The following image shows the result of SA-Gate segmentation.
Figure 1. SA-Gate segmentation Test Example 1
Figure 2. SA-Gate segmentation Test Example 2
Figure 3. SA-Gate segmentation Test Example 3
The following table lists the SA-Gate models supported by the Vitis AI Library.
| No | Model Name | Framework |
|---|---|---|
| 1 | SA_gate_pt | PyTorch |