metadata
license: mit
tags:
- LIQUID
- PENETRANT
- TEST
- INSPECTION
- DETECTION
Liquid Penetrant Test (DP, LPI, PT)
Detection of liquid penetrant test with AI (Yolo11)
Supported Labels
['defecto']
ALL my models YOLO11, 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