SSCMA-Micro
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Published
20 hours ago •
Seeed-Studio
Seeed-Studio
A cross-platform framework that deploys and applies SSCMA models to microcontrol devices
SSCMA-Micro CPP SDK
SSCMA-Micro is a cross-platform machine learning inference framework designed for embedded devices, serving for Seeed Studio SenseCraft Model Assistant and providing functionalities such as digital image processing, neural network inferencing, AT command interaction, and more.
Overview
Neural Networks
| Object Detection | Classification | Pose Detection | Segmentation | Anomaly Detection |
|---|---|---|---|---|
| FOMO | IMCLS (MobileNetV2) | PFLD | YOLOv11 Seg | |
| Swift YOLO (YOLOv5) | IMCLS (MobileNetV4) | YOLOv8 Pose | ||
| YOLOv8 | YOLOv11 Pose | |||
| YOLOv11 | ||||
| YOLO World | ||||
| Nidia Det | ||||
| RTMdet |
Model Formats
| TF-Lite | ONNX | Binary Model |
|---|---|---|
| INT8 | HEF Model | |
| UINT8 | CVI Model | |
| UINT16 | ||
| FLOAT32 |
Device Support
| MCUs | SBCs |
|---|---|
| Espressif ESP32S3 EYE | Hailo AI (Raspberry Pi) |
| Seeed Studio XIAO (ESP32S3) | |
| Seeed Studio Grove Vision AI V1 | |
| Seeed Studio Grove Vision AI V2 | |
| Seeed Studio SenseCAP Watcher | |
| Seeed Studio reCamera |
License
This project is released under the Apache License.
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Seeed-Studio
Metadata
A cross-platform framework that deploys and applies SSCMA models to microcontrol devices