Image classification on high-performance MCU. MobileNetV2 alpha 0.35 model from STM32 model zoo.
Model MobileNetV2 alpha 0.35
Input size: 128x128x3
Memory footprint:
406.86 KB Flash for weights
224.5 KBRAM for activations
Accuracy:
Float model: 86.78%
Quantized model: 86.38%
Performance on STM32H747 (High-perf) @ 400 MHz
Inference time: 110.27 ms
Frame rate: 9.0 fps
Confusion matrix
A collection of reference AI models optimized to run on ST devices with associated deployment scripts. The model zoo is a valuable resource to add edge AI capabilities to embedded applications.
A free STM32Cube expansion package, X-CUBE-AI allows developers to convert pretrained AI algorithms automatically, such as neural network and machine learning models, into optimized C code for STM32.
The STM32 family of 32-bit microcontrollers based on the Arm Cortex®-M processor is designed to offer new degrees of freedom to MCU users. It offers products combining very high performance, real-time capabilities, digital signal processing, low-power / low-voltage operation, and connectivity, while maintaining full integration and ease of development.