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The previous commit was meant to remove .github/workflows and removed every tracked path instead — 892 files, the whole repo. This puts back the 874 that were never in scope; the eighteen workflow files stay gone, for the reasons that commit gives. Content is byte-identical to 9d2aec9 outside .github/workflows.
46 lines
1.0 KiB
Python
46 lines
1.0 KiB
Python
# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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"""Example showing how to use the EfficientAd model.
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EfficientAd is a fast and accurate model for anomaly detection,
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particularly well-suited for industrial inspection tasks.
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"""
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from anomalib.data import MVTecAD
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from anomalib.engine import Engine
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from anomalib.models import EfficientAd
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# 1. Basic Usage
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# Initialize with default settings
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model = EfficientAd()
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# 2. Custom Configuration
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# Configure model parameters
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model = EfficientAd(
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teacher_out_channels=384, # Number of teacher output channels
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model_size="m",
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lr=1e-4,
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)
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# 3. Training Pipeline
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# Set up the complete training pipeline
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datamodule = MVTecAD(
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root="./datasets/MVTecAD",
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category="bottle",
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train_batch_size=32,
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)
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# Initialize training engine with specific settings
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engine = Engine(
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max_epochs=20,
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accelerator="auto", # Automatically detect GPU/CPU
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devices=1, # Number of devices to use
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)
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# Train the model
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engine.fit(
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model=model,
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datamodule=datamodule,
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)
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