Applicable for | STM32MP13x lines, STM32MP15x lines, STM32MP25x lines |
1. Application samples[edit | edit source]
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NPU/GPU | CPU | CPU | EdgeTPU | |
![]() Image classification |
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![]() Object detection |
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![]() Pose estimation |
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![]() Semantic segmentation |
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![]() Face recognition |
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1 NPU/GPU acceleration based on OpenVX backend using network binary graph (NBG) is available only for STM32MP2x boards |
2. Performance Comparison[edit | edit source]
Model | STM32MP25 NPU |
STM32MP15x CPU | |
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![]() Image classification |
MobilenetV1_0.5 128x128 |
515 FPS |
22 FPS |
MobilenetV2_1.0 224x224 |
72 FPS |
2 FPS | |
![]() Object detection |
SSD_MobilenetV1_1.0 300x300 |
40 FPS |
2 FPS |
SSD_MobilenetV2_FPNLite 224x224 | 36 FPS | 0.8 FPS | |
![]() Face recognition |
Blazeface + Facenet |
33 FPS |
1.5 FPS |
![]() Pose estimation |
YoloV8n 256x256 |
59 FPS |
1.3 FPS |
![]() Semantic segmentation |
DeepLabV3 257x257 |
17 FPS |
1 FPS |
Neural processing unit - NEW
Graphics processing units
Central processing unit
Frames per second