Fluorescent penetrant inspection (FPI, DP, LPI, PT)

Detection of liquid penetrant test with AI (Yolo11)

MODEL

• Yolo11l: https://huggingface.co/jparedesDS/liquid-penetrant-test-detection

Supported Labels

['defecto']

ALL my models YOLOv10 & YOLOv9

• Yolov9c: https://huggingface.co/jparedesDS/cs2-yolov9c
• Yolov10s: https://huggingface.co/jparedesDS/cs2-yolov10s
• Yolov10m: https://huggingface.co/jparedesDS/cs2-yolov10m
• Yolov10b: https://huggingface.co/jparedesDS/cs2-yolov10b
• Yolov10b: https://huggingface.co/jparedesDS/valorant-yolov10b
• Yolo11x: https://huggingface.co/jparedesDS/welding-defects-detection

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

Labels

Results

Predict

YOLO11l summary (fused): 464 layers, 25,280,083 parameters, 0 gradients, 86.6 GFLOPs
                 Class     Images  Instances      Box(P          R      mAP50  mAP50-95): 100%|██████████| 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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