- This allows for face detection, face recognition, facial landmark detection, object detection and AI Voice. One or more engines can run in parallel inside VIP9000 together with user defined AI programs, due to VIP9000's native multi-task, multi-context support.
VIP9000 supports all popular deep learning frameworks (including TensorFlow, Pytorch, TensorFlow Lite, Caffe, Caffe2, DarkNet, ONNX, NNEF, and Keras) as well as programming APIs like OpenCL and OpenVX. Neural network optimization techniques such as quantization, pruning, and model compression are also supported natively with the VIP9000 architecture.
AI applications can be easily ported to VIP9000 platforms through offline conversion by Vivante ACUITYTM SDK, or through run-time interpretation with Android NN, NN API, or ARM NN.