TensorFlow Lite-Anwendungen
R2025bGenerieren von Code für Deep-Learning-Netzwerke für Inferenz mithilfe der TFLite-Bibliothek
Generieren Sie Code für Inferenz mithilfe der TFLite-Bibliothek und Bereitstellen auf eingebetteten Zielen.
Enthaltene Beispiele
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.
Deploy Pose Estimation Application Using TensorFlow Lite Model (TFLite) Model on Host and Raspberry Pi
Simulate and generate code for a human pose estimation TFLite model.
Deploy Super Resolution Application That Uses TensorFlow Lite (TFLite) Model on Host and Raspberry Pi
Generate code for a super resolution application that uses a TFLite model for inference.
Audio Event Classification Using TensorFlow Lite on Raspberry Pi
Perform audio event classification on Raspberry Pi® using the YAMNet pretrained deep neural network from the TensorFlow Lite library.
