Sheena / Diabetic Retinopathy Blindness Detection
This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.
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.
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.
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.
Download block output
Title | Type | Size | |
---|---|---|---|
Image training data | NPY file | 2427 windows | |
Image training labels | NPY file | 2427 windows | |
Image testing data | NPY file | 200 windows | |
Image testing labels | NPY file | 200 windows | |
NN Classifier model | TensorFlow Lite (float32) | 525 KB | |
NN Classifier model | TensorFlow Lite (int8 quantized) | 136 KB | |
NN Classifier model | TensorFlow Lite (int8 quantized with float32 input and output) | 136 KB | |
NN Classifier model | TensorFlow SavedModel | 499 KB |
Summary
Data collected
2,613 itemsProject info
Project ID | 41896 |
Project version | 2 |
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