TexasInstruments / edgeai-tensorlab

Edge AI Model Development Tools
https://github.com/TexasInstruments/edgeai
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edgeai-tensorlab

Edge AI model training, quantization, compilation/benchmark & Model Zoo

Notice

Our documentation landing pages are the following:


Release Notes

Please see the release notes


Components

Category Tool/Link Purpose IS NOT
List of recommended models and associated information edgeai-modelzoo Provides collection of pretrained models
Model optimization tools for model training Model optimization tools Model optimization tools
- Model surgery: Modifies models with minimal loss in accuracy and makes it suitable for TI device (replaces unsupported operators)
- Model Pruning/sparsity: Induces sparsity during training – only applicable for specific devices
- QAT: Quantization Aware Training to improve accuracy with fixed point quantization
- Does not support Tensorflow
Model compilation, accuracy and performance benchmarking edgeai-benchmark Bring your own model and compile, benchmark and generate artifacts for deployment on SDK with camera, inference and display (using edgeai-gst-apps)
- Comprehends inference pipeline including dataset loading, pre-processing and post-processing
- Benchmarking of accuracy and latency with large data sets
- Post training quantization
- Docker for easy development environment setup
Model training tools edgeai-torchvision
edgeai-mmdetection
edgeai-yolox
edgeai-mmdetection3d
Training repositories for various tasks
- Provides extensions of popular training repositories (like mmdetection, yolox) with lite version of models
- Does not support Tensorflow
Example datasets edgeai-datasets Example datasets
End-to-End model development; Bring your own data. Integrates several of the above tools. edgeai-modelmaker (Model Maker) Integrated, Command line environment for training & compilation
- Bring your own data, select a model, perform training and generate artifacts for deployment on SDK
- Backend for the GUI tool Model Composer (early availability of features compared to Model Composer).
- For novice users, GUI based Model Composer is recommended instead of Model Maker.
- Does not support Bring Your Own Model workflow