NVIDIA Jetson Xavier NX - Demonstration : Running multiple Networks Simultaneously

We run the demo Cloud Native applications on the NVIDIA Jetson Xavier NX. The NVIDIA demo uses the following containers to achieve this: 1. DeepStream Container with people detection - A Resnet-18 model with input image size of 960 x 544 x 3. This model was converted from TensorFlow to TensorRT 2. Pose container with pose detection - Resnet-18 model with input image resolution of 224 x 224. The model was converted from PyTorch to Tensor RT 3. Gaze Container - MTCNN model for face detection with input image resolution of 260X135. The model was converted from Caffe to TensorRT - NVIDIA Facial landmarks model with input resolution of 80X80 per face. The model was converted from TensorFlow to TensorRT - NVIDIA Gaze model with input resolution of 224X224 per left eye, right eye and whole face. The model was converted from TensorFlow to TensorRT 4. Voice Container with speech recognition and Natural Language Processing - Quartznet-15X5 model for speech recognition which was converted from PyTorch to TensorRT. - BERT Base model for language model for NLP which was converted from TensorFlow to TensorRT.