Nathaniel Felleke / Trash Image Detection
This is your Edge Impulse project. From here you acquire new training data, design impulses and train models.
About this project
Mapping Litter in Cities
A prototype of a roadside litter detection device that maps trash in cities and helps locate pickup locations. Using an image recognition model made in Edge Impulse Studio, the device is able to classify whether images of the road contain trash or not. If there is trash, a Blues Wireless Notecard retrieves the GPS location and transmits the classification to the cloud.
Creating your first impulse (100% complete)
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.
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.
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Data collected972 items
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