来自外部平台的预训练网络
从 TensorFlow™ 2、TensorFlow-Keras、PyTorch®、ONNX™(开放式神经网络交换)模型格式和 Caffe 中导入网络和层图。有关详细信息,请参阅预训练的深度神经网络和Interoperability Between Deep Learning Toolbox, TensorFlow, PyTorch, and ONNX。
您必须有支持包才能在 Deep Learning Toolbox™ 中运行导入函数。如果未安装支持包,则每个函数都会在附加功能资源管理器中提供对应支持包的下载链接。建议将支持包下载到您正在运行的 MATLAB® 版本的默认位置。您也可以从以下链接直接下载支持包。
importNetworkFromONNX
函数需要 Deep Learning Toolbox Converter for ONNX Model Format。要下载支持包,请转至 https://www.mathworks.com/matlabcentral/fileexchange/67296-deep-learning-toolbox-converter-for-onnx-model-format。importNetworkFromPyTorch
函数需要 Deep Learning Toolbox Converter for PyTorch Models。要下载支持包,请转至 https://www.mathworks.com/matlabcentral/fileexchange/111925-deep-learning-toolbox-converter-for-pytorch-models。importNetworkFromTensorFlow
函数需要 Deep Learning Toolbox Converter for TensorFlow Models。要下载支持包,请转至 https://www.mathworks.com/matlabcentral/fileexchange/64649-deep-learning-toolbox-converter-for-tensorflow-models。
函数
主题
导入
- Interoperability Between Deep Learning Toolbox, TensorFlow, PyTorch, and ONNX
Learn how to import networks from TensorFlow, PyTorch, and ONNX and use the imported networks for common Deep Learning Toolbox workflows. Learn how to export networks to TensorFlow and ONNX. - Tips on Importing Models from TensorFlow, PyTorch, and ONNX
Tips on importing Deep Learning Toolbox networks from TensorFlow, PyTorch, and ONNX. - Import PyTorch® Model Using Deep Network Designer
This example shows how to import a PyTorch® model interactively by using the Deep Network Designer app. (自 R2023b 起) - 预训练的深度神经网络
了解如何下载和使用预训练的卷积神经网络进行分类、迁移学习和特征提取。 - Inference Comparison Between TensorFlow and Imported Networks for Image Classification
Perform prediction in TensorFlow with a pretrained network, import the network into MATLAB usingimportTensorFlowNetwork
, and then compare inference results between TensorFlow and MATLAB networks. - Inference Comparison Between ONNX and Imported Networks for Image Classification
Perform prediction in ONNX with a pretrained network, import the network into MATLAB usingimportONNXNetwork
, and then compare inference results between ONNX and MATLAB networks. - 基于预训练的 Keras 层组合网络
此示例说明如何从预训练的 Keras 网络中导入层、用自定义层替换不支持的层,以及将各层组合成可以进行预测的网络。 - Replace Unsupported Keras Layer with Function Layer
This example shows how to import the layers from a pretrained Keras network, replace the unsupported layers with function layers, and assemble the layers into a network ready for prediction. - Classify Images in Simulink with Imported TensorFlow Network
Import a pretrained TensorFlow network usingimportTensorFlowNetwork
, and then use the Predict block for image classification in Simulink®. - Deploy Imported TensorFlow Model with MATLAB Compiler
Import third-party pretrained networks and deploy the networks using MATLAB Compiler™. - Select Function to Import ONNX Pretrained Network
Import an ONNX pretrained network usingimportONNXNetwork
,importONNXLayers
, orimportONNXFunction
. - View Autogenerated Custom Layers Using Deep Network Designer
This example shows how to import a pretrained TensorFlow™ network and view the autogenerated layers in Deep Network Designer.
自定义层
- 定义自定义深度学习层
了解如何定义自定义深度学习层。 - Define Custom Deep Learning Intermediate Layers
Learn how to define custom deep learning intermediate layers. - Define Custom Deep Learning Output Layers
Learn how to define custom deep learning output layers.
相关信息
- https://www.mathworks.com/matlabcentral/fileexchange/67296-deep-learning-toolbox-converter-for-onnx-model-format
- https://www.mathworks.com/matlabcentral/fileexchange/64649-deep-learning-toolbox-converter-for-tensorflow-models
- https://www.mathworks.com/matlabcentral/fileexchange/111925-deep-learning-toolbox-converter-for-pytorch-models
- https://www.mathworks.com/matlabcentral/fileexchange/61735-deep-learning-toolbox-importer-for-caffe-models