Analytics for TI's Application Specific Microcontrollers (MCUs)
The table below provides detailed explanation of each of the tools:
| Category | Tool/Link | Purpose | IS NOT |
|---|---|---|---|
| Edge AI Studio Model Composer | Edge AI Studio Model Composer | GUI based, No-Code AI development for MCUs and MPUs - Data Capture, Annotation, Model Training, Compilation and Live Preview (MCU support coming in Nov 2024) | |
| Tiny ML Model development for MCUs | tinyml-tensorlab | Commandline based development for advanced users - Model Zoo, ModelMaker, Model Optimization Tools, Model training, compilation, examples and other tools. Browse the link for detailed documentation. | |
| Software Development Kit for MCUs | Devices & SDKs | SDK for compatible devices. Run ML inference on device. | |
| Neural Network Compilation Tools for MCUs | Neural Network Compiler for MCUs | Compile Neural Network Models for accelerated inference in TI MCUs |
- [2025-January] Major feature updates (version 1.0.0) of the software
- Tiny ML Modelmaker is now a pip installable package!
- Feature Extraction transforms are now modular and compatible with C2000Ware 5.05 only
- Multiclass ROC-AUC graphs are autogenerated for better explainability of reports and help select thresholds based on false alarm/ sensitivity preference
- Run now begins with displaying inference time, sram usage and flash usage for all the devices for any model.
- Supports Haar and Hadamard Transform
- Golden test vectors file has one set uncommented by default to work OOB
- Existing models can be modified on the fly through a config file (check Tiny ML Modelmaker docs)
- PCA graphs are auto plotted for feature extracted data → Helps in identifying if the feature extraction actually helped
- [2024-November] Updated (version 0.9.0) of the software
- [2024-August] Release version 0.8.0 of the software
- [2024-July] Release version 0.7.0 of the software
- [2024-June] Release version 0.6.0 of the software
- [2024-May] First release (version 0.5.0) of the software