Kutluhan Aktar / IoT AI-driven Smart Grocery Cart
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About this project
This object detection (FOMO) model detects a small group of food retail products by utilizing the product brand names as labels:
- Barilla
- Milk
- Nutella
- Pringles
- Snickers
After building my object detection (FOMO) model, I deployed my model as an OpenMV firmware and flashed OpenMV Cam H7 with the generated firmware so as to run inferences.
Download block output
| Title | Type | Size | |
|---|---|---|---|
| Image training data | NPY file | 60 windows | |
| Image training labels | JSON file | 60 windows | |
| Image testing data | NPY file | 10 windows | |
| Image testing labels | JSON file | 10 windows | |
| Object detection model | TensorFlow Lite (float32) | 82 KB | |
| Object detection model | TensorFlow Lite (int8 quantized) | 56 KB | |
| Object detection model | TensorFlow SavedModel | 187 KB | |
| Object detection model | Keras h5 model | 88 KB |
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Summary
Data collected
70 itemsProject info
| Project ID | 166688 |
| Project version | 1 |
| License | Apache 2.0 |
