What is it¶
nnio is a light-weight python package for easily running neural networks.
It supports running models on CPU as well as some of the edge devices:
For each device there exists an own library and a model format. We wrap all those in a single well-defined python package.
Look at this simple example:
import nnio # Create model and put it on a Google Coral Edge TPU device model = nnio.EdgeTPUModel( model_path='path/to/model_quant_edgetpu.tflite', device='TPU', ) # Create preprocessor preproc = nnio.Preprocessing( resize=(224, 224), batch_dimension=True, ) # Preprocess your numpy image image = preproc(image_rgb) # Make prediction class_scores = model(image)
nnio was developed for the Fast Sense X microcomputer. It has six neural accelerators, which are all supported by nnio:
nnio is simply installed with pip, but it requires some additional libraries. See Installation.
There are 3 ways one can use nnio:
Loading your saved models for inference - Basic Usage
Using already prepared models from our model zoo: Model Zoo
Using our API to wrap around your own custom models. Extending nnio
- Basic Usage
- Model Zoo
- Extending nnio