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Liquid Penetrant Test (DP, LPI, PT)

Detection of liquid penetrant test with AI (Yolo11)

Supported Labels

['defecto']

ALL my models YOLO11, YOLOv10 & YOLOv9

How to use

from ultralytics import YOLO

# Load a pretrained YOLO model
model = YOLO(r'weights\yolo11l_LPI.pt')

# Run inference on 'image.png' with arguments
model.predict(
    'image.png',
    save=True,
    device=0
    )

Confusion matrix normalized

confusion_matrix_normalized.png

Labels

labels.jpg

Results

results.png

Predict

val_batch1_labels.jpg val_batch2_labels.jpg

YOLO11l summary (fused): 464 layers, 25,280,083 parameters, 0 gradients, 86.6 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 12/12 [00:05<00:00,  2.32it/s]
                   all        836        752      0.794      0.771      0.793      0.379

Others models...

https://huggingface.co/jparedesDS/welding-defects-detection

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Collection including jparedesDS/fluorescent-penetrant-inspection