Caffe Framework
The Vitis™ AI Library contains the following neural network libraries based on the Caffe framework:
TensorFlow Framework
The Vitis™ AI contains the following neural network libraries based on the TensorFlow framework:
PyTorch Framework
The Vitis™ AI supports the following type of neural network libraries based on the PyTorch framework.
- Classification
- ReID Detection
- Face Recognition
- Semantic Segmentation
- Pointpillars
- Medical Segmentation
- 3D Segmentation
- Pointpillars_nuscenes: Surround-view
- Centerpoint: 4D radar-based 3D detection
- PointPainting: Image-lidar sensor fusion
- Depth Estimation
- Bayesian Crowd Counting
- MultiTask V3
- Polyp Segmentation
- UltraFast Road Line Detection
- FairMot
- PSMNet
- SOLO
- CLOCs
The related libraries are open-source and can be modified as needed. The open-source codes are available on GitHub.
The Vitis™ AI Library provides image test samples and video test samples for all the above networks. In addition, the kit provides the corresponding performance test program. For video-based testing, use the raw video for evaluation. Decoding by software libraries on Arm® processors may have inconsistent decoding time, which may affect the accuracy of evaluation.