LOL1256 / C1 Public
Target: Espressif ESP-EYE (ESP32 240MHz) Clone this project

Test data

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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.

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Sample name Expected outcome Accuracy Result
20250427183715 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183659 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183626 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183612 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183553 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183537 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183522 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183504 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427183456 100 100% 1 100
Show classification Show in data acquisition Show in feature explorer
20250427184111 500 0% 1 uncertain
Show classification Show in data acquisition Show in feature explorer
20250427184051 500 100% 1 500
Show classification Show in data acquisition Show in feature explorer
20250427184012 500 100% 1 500
Show classification Show in data acquisition Show in feature explorer
20250427184030 500 100% 1 500
Show classification Show in data acquisition Show in feature explorer
20250427183901 500 100% 1 500
Show classification Show in data acquisition Show in feature explorer
20250427184811 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184816 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184759 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184743 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184414 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184354 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184312 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184242 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427184149 20 100% 1 20
Show classification Show in data acquisition Show in feature explorer
20250427183314 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183312 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183306 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183300 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183235 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183220 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183202 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183125 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183039 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183145 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
20250427183059 200 100% 1 200
Show classification Show in data acquisition Show in feature explorer
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Model testing output

Results

Model version:
Accuracy
97.06%

Metrics for Classifier

Metric Value
Area under ROC Curve 1.00
Weighted average Precision 0.97
Weighted average Recall 0.97
Weighted average F1 score 0.97

Confusion matrix

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Feature explorer

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