图像分类和分割应用程序
为执行图像分类和分割的深度学习网络生成代码
为图像分类和分割应用程序生成代码，并部署在嵌入式目标上。
精选示例
Generate Code for a Deep Learning Network for x86-64 Platforms Using Advanced Vector Instructions
Generate code for deep learning networks, targeting an Intel® processor.
生成代码并将 SqueezeNet 网络部署到 Raspberry Pi
当您没有硬件支持包时使用 ARM® Compute Library 生成代码。
通过 ARM 计算使用 codegen 进行深度学习预测
为深度学习网络生成要部署到 ARM 处理器的代码。
Generate Code and Deploy MobileNet-v2 Network to Raspberry Pi
Use the MobileNet-V2 network for object prediction on external hardware.
Code Generation for Semantic Segmentation Application on ARM Neon Targets That Uses U-Net
Generate a static library that performs image segmentation by using the deep learning network U-Net on ARM targets.
Generate Code for TensorFlow Lite (TFLite) Model and Deploy on Raspberry Pi
Generate code that uses a TensorFlow™ Lite model for inference.
Deploy Classification Application Using Mobilenet-V3 TensorFlow Lite Model on Host and Raspberry Pi
Generate code for a classification segmentation application that uses TensorFlow Lite model.
Deploy Semantic Segmentation Application Using TensorFlow Lite Model on Host and Raspberry Pi
Generate code for an image segmentation application that uses TensorFlow Lite model.
