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--- |
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pipeline_tag: object-detection |
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tags: |
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- welding |
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- defects |
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- detection |
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--- |
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# Welding Defects Detector |
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#### Supported Labels |
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['Defect', 'Welding Line', 'Workpiece', 'porosity'] |
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#### How to use |
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``` |
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from ultralytics import YOLO |
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# Load a pretrained YOLO model |
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model = YOLO(r'weights\welding_defects_yolo11x.pt') |
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# Run inference on 'image.png' with arguments |
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model.predict( |
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'image.png', |
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save=True, |
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device=0 |
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) |
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``` |
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#### Confusion matrix normalized |
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![confusion_matrix_normalized.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/gflYDiDQL4P8ZUiij7Fnp.png) |
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#### Labels |
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![labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/0ZIgleo87QYeOBP4swPJj.jpeg) |
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![labels_correlogram.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/bHGE-LOjH4jgmbBShGZvC.jpeg) |
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#### Results |
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![results.png](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/83-tr_zbyudVR3EnRW6VU.png) |
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#### Predict |
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![val_batch0_labels.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/13x44dJn8_6rSgm7eEXRz.jpeg) |
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![val_batch0_pred.jpg](https://cdn-uploads.huggingface.co/production/uploads/62e1c9b42e4cab6e39dafc97/8luLKVm-7OSvwfkDXV27x.jpeg) |
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``` |
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YOLO11x summary (fused): 464 layers, 56,831,644 parameters, 0 gradients, 194.4 GFLOPs |
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Class Images Instances Box(P R mAP50 mAP50-95): 100%|ββββββββββ| 7/7 [00:06<00:00, 1.11it/s] |
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all 116 773 0.826 0.827 0.842 0.632 |
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Defect 56 131 0.552 0.427 0.445 0.202 |
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Welding Line 116 294 0.873 0.966 0.966 0.679 |
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Workpiece 110 307 0.941 0.987 0.992 0.938 |
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porosity 35 41 0.939 0.927 0.965 0.71 |
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Speed: 0.5ms preprocess, 26.3ms inference, 0.0ms loss, 2.9ms postprocess per image |
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``` |
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#### Others models... |
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https://huggingface.co/jparedesDS/ |