Nilanjan Mandal / Wounded Animal Detection Public
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Nilanjan Mandal / Wounded Animal Detection

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

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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.

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
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 items

Project info

Project ID 90956
Project version 1
License No license attached