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README.md
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- anomaly-detection
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license: apache-2.0
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library_name: pytorch
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# Wheat Anomaly Detection Model
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This model is a PyTorch-based ResNet model trained to detect anomalies in wheat crops, such as diseases, pests, and nutrient deficiencies.
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outputs = model(inputs)
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predicted_class = torch.argmax(outputs.logits, dim=1)
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print(f"Predicted Class: {predicted_class.item()}")
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- anomaly-detection
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license: apache-2.0
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library_name: pytorch
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datasets:
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- your_huggingface_username/your_dataset_name
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---
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# Wheat Anomaly Detection Model
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This model is a PyTorch-based ResNet model trained to detect anomalies in wheat crops, such as diseases, pests, and nutrient deficiencies.
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outputs = model(inputs)
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predicted_class = torch.argmax(outputs.logits, dim=1)
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print(f"Predicted Class: {predicted_class.item()}")
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