Louis (Demo) / Fitness classifier Public
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Louis (Demo) / Fitness classifier

This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.

Accelerometer

Creating your first impulse (100% complete)

Acquire data

Every Machine Learning project starts with data. You can capture data from a development board or your phone, or import data you already collected.

Let's collect some data

Design an impulse

Teach the model to interpret previously unseen data, based on historical data. Use this to categorize new data, or to find anomalies in sensor readings.

Getting started: Continuous motion recognition
Getting started: Responding to your voice
Getting started: Adding sight to your sensors

Deploy

Package the complete impulse up, from signal processing code to trained model, and deploy it on your device. This ensures that the impulse runs with low latency and without requiring a network connection.

Deploy your model

Download block output

Title Type Size
Spectral features training data NPY file 9193 windows
Spectral features training labels NPY file 9193 windows
Spectral features testing data NPY file 2808 windows
Spectral features testing labels NPY file 2808 windows
NN Classifier model (version #1) TensorFlow Lite (float32) 5 KB
NN Classifier model (version #1) TensorFlow Lite (int8 quantized) 3 KB
NN Classifier model (version #1) TensorFlow Lite (int8 quantized with float32 input and output) 5 KB
NN Classifier model (version #1) TensorFlow SavedModel 11 KB
NN Classifier model (version #1) Keras h5 model 5 KB
NN Classifier model (version #2) TensorFlow Lite (float32) 5 KB
NN Classifier model (version #2) TensorFlow Lite (int8 quantized) 3 KB
NN Classifier model (version #2) TensorFlow Lite (int8 quantized with float32 input and output) 4 KB
NN Classifier model (version #2) TensorFlow SavedModel 16 KB
NN Classifier model (version #3) TensorFlow Lite (float32) 6 KB
NN Classifier model (version #3) TensorFlow Lite (int8 quantized) 4 KB
NN Classifier model (version #3) TensorFlow Lite (int8 quantized with float32 input and output) 4 KB
NN Classifier model (version #3) TensorFlow SavedModel 16 KB

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Summary

Data collected
17m 45s

Project info

Project ID 36037
Project version 3
License Apache 2.0