Edge Impulse Experts / Big Components Inspection Public
Target: Arduino UNO Q (Qualcomm QRB2210) Clone this project

Test data

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Model variants
No additional model variants available Test 'Unoptimized (float32)' 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 Precision score Result
WIN_20260928_09_51_49_Pro C1N, C2N, IN, PN, SN, UN 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_51_45_Pro C1N, C2N, IN, PN, SN, UN 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_51_31_Pro C1N, C2N, IN, PN, SN, UN 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_48_06_Pro C1A, C2A, IA, PA, SA, UA 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_47_46_Pro C1A, C2A, IA, PA, SA, UA 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_46_50_Pro C1A, C2A, IA, PA, SA, UA 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_46_46_Pro C1A, C2A, IA, PA, SA, UA 100%
Show classification Show in data acquisition Show in feature explorer
WIN_20260928_09_43_59_Pro C1A, C2A, IA, PA, SA, UA 100%
Show classification Show in data acquisition Show in feature explorer
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Model testing output

Results

Model version:
mAP@50
1.00

Metrics for Pretrained learn

Metric Value
mAP 0.91
mAP@[IoU=50] 1.00
mAP@[IoU=75] 1.00
mAP@[area=small] -1.00
mAP@[area=medium] 0.91
mAP@[area=large] 0.92
Recall@[max_detections=1] 0.92
Recall@[max_detections=10] 0.92
Recall@[max_detections=100] 0.92
Recall@[area=small] -1.00
Recall@[area=medium] 0.91
Recall@[area=large] 0.93
Precision score (legacy) 100.0%

Confusion matrix

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Feature explorer

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