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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.
48 lines
1.3 KiB
Python
48 lines
1.3 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 Patchcore model.
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Patchcore is a memory-based model that uses a pretrained CNN backbone
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to extract and store patch features for anomaly detection.
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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 Patchcore
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# 1. Basic Usage
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# Initialize with default settings
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model = Patchcore()
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# 2. Custom Configuration
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# Configure model parameters
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model = Patchcore(
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backbone="wide_resnet50_2", # Feature extraction backbone
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layers=["layer2", "layer3"], # Layers to extract features from
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pre_trained=True, # Use pretrained weights
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num_neighbors=9, # Number of nearest neighbors
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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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eval_batch_size=32, # Important for feature extraction
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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=1, # Patchcore typically needs only one epoch
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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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