Revision as of 12:30, 24 June 2020 by Registered User (Created page with "==Article purpose== This article aims to describe how to run an inference on the STM32MP1 using a Google Coral EdgeTPU device and the Python TensorFlow-Lite API. {{info|The...")
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There are 1 incomplete or pending task to finish installation of Semantic MediaWiki. An administrator or user with sufficient rights can complete it. This should be done before adding new data to avoid inconsistencies.1. Article purpose[edit source]
This article aims to describe how to run an inference on the STM32MP1 using a Google Coral EdgeTPU device and the Python TensorFlow-Lite API.
2. Difference between TensorFlow-Lite Python APIs[edit source]
The Artificial Intelligence expansion package X-LINUX-AI comes with two versions of TensorFlow-Lite. The first runtime version is based on the release 2.2.0 of TensorFlow and the second is runtime based on XXX. This is due to the fact that TensorFlow Lite[1]2.2.0 does not support the Coral EdgeTPU runtime. The following figure explains the software structure.
- Example.jpg
Caption1
3. Running an inference using XXXX[edit source]
Before running the inference make sure that your .tflite model is compiled for inferencing on the Coral EdgeTPU. Please take a look on how to Compile your custom model and send it to the board.