Nilanjan Mandal / Wounded Animal Detection
This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.
About this project
Wounded animal detection in wild using Kria KV260 and Edge Impulse
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 | 73 windows | |
| Image training labels | NPY file | 73 windows | |
| Image testing data | NPY file | 19 windows | |
| Image testing labels | NPY file | 19 windows | |
| Transfer learning model | TensorFlow Lite (float32) | 2 MB | |
| Transfer learning model | TensorFlow Lite (int8 quantized) | 666 KB | |
| Transfer learning model | TensorFlow SavedModel | 2 MB | |
| Transfer learning model | Keras h5 model | 2 MB |
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Summary
Data collected
92 itemsProject info
| Project ID | 90956 |
| Project version | 1 |
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