Image Classification
TensorBoard
English
ultralytics
Tyre Quality
Tyre Classification
Image Classification
Machine Learning
Pytorch
Deep Learning
Computer Vision
Prediction
yolov8
yolo
TyreInspection
QualityControl
DefectDetection
AutomotiveAI
SafetyStandards
IndustrialAI
AIQualityAssessment
PredictiveMaintenance
AIModel
Eval Results
nehulagrawal
commited on
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Update README.md
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README.md
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@@ -97,6 +97,8 @@ pip install ultralyticsplus==0.0.28 ultralytics==8.0.43
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```python
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from ultralyticsplus import YOLO, render_result
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# load model
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model = YOLO('foduucom/Tyre-Quality-Classification-AI')
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model.overrides['max_det'] = 1000 # maximum number of detections per image
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# set image
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image = '/
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# perform inference
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results = model
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# observe results
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top_class_index = results[0].probs.
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Class = model.names[top_class_index]
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print(Class)
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```python
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from ultralyticsplus import YOLO, render_result
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import torch
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# load model
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model = YOLO('foduucom/Tyre-Quality-Classification-AI')
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model.overrides['max_det'] = 1000 # maximum number of detections per image
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# set image
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image = '/content/90-100-10-ceat-500x500.jpeg'
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# perform inference
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results = model(image)
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# observe results
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top_class_index = torch.argmax(results[0].probs).item()
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Class = model.names[top_class_index]
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print(Class)
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