Nathaniel Felleke / Trash Image Detection
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Maintenance window planned next Monday, 04/29 at 5:00AM UTC (more)
About this project
Mapping Litter in Cities
Introduction
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.
Hackster.io Project
Download block output
| Title | Type | Size | |
|---|---|---|---|
| Image training data | NPY file | 764 windows | |
| Image training labels | NPY file | 764 windows | |
| Image testing data | NPY file | 208 windows | |
| Image testing labels | NPY file | 208 windows | |
| Transfer learning model | TensorFlow Lite (float32) | 2 MB | |
| Transfer learning model | TensorFlow Lite (int8 quantized) | 625 KB | |
| Transfer learning model | TensorFlow SavedModel | 2 MB | |
| Transfer learning model | Keras h5 model | 2 MB |
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Summary
Data collected
972 itemsProject info
| Project ID | 110140 |
| Project version | 4 |
| License | No license attached |
