Kutluhan Aktar / IoT AI-driven Smart Grocery Cart Public
Target: Cortex-M4F 80MHz Clone this project

Test data

Set confidence thresholds
Model variants
Test 'Unoptimized (float32)' model Test 'Quantized (int8)' model
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.
Sample name Expected outcome F1 score Result
Food.2022_12_7_15-48-25 pringles 100%
Show classification Show in data acquisition
Food.2022_12_7_15-48-5 pringles 100%
Show classification Show in data acquisition
Food.2022_12_7_15-47-15 snickers 0%
Show classification Show in data acquisition
Food.2022_12_7_15-47-45 nutella 100%
Show classification Show in data acquisition
Food.2022_12_7_15-47-25 nutella 100%
Show classification Show in data acquisition
Food.2022_12_7_15-47-2 snickers 100%
Show classification Show in data acquisition
Food.2022_12_7_15-45-55 barilla 100%
Show classification Show in data acquisition
Drink.2022_12_7_15-41-3 milk 100%
Show classification Show in data acquisition
Food.2022_12_7_15-45-30 barilla 100%
Show classification Show in data acquisition
Drink.2022_12_7_15-40-55 milk 100%
Show classification Show in data acquisition

Model testing output

Results

Model version:
Accuracy
90.00%

Confusion matrix

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Feature explorer

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