Summary

This chapter introduced the ONNX model format and the platforms and frameworks that support it. This framework helps Detectron2 models to be interoperable with different frameworks and platforms. It then provides the steps to export Detectron2 models to this format and the code to deploy the exported model in the browser environments. This chapter also introduced D2Go, a framework for training, optimizing, and deploying neural networks for computer vision applications with minimal memory storage and computation resources. Additionally, its models are prepared to be further optimized using the quantization technique, which converts the model weights and activations in lower-precision number systems. This quantization step further reduces the model memory requirement and improves computation performance. Therefore, D2Go models are suitable for deploying into mobile or edge devices. D2Go also has pre-trained models on its Model Zoo. Thus, this chapter provides the steps to build...