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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
1.4 KiB
Python
46 lines
1.4 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 your own dataset with Anomalib.
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This example demonstrates how to use a custom folder dataset where images
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are organized in a specific directory structure.
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"""
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from pathlib import Path
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from anomalib.data import Folder
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# 1. Basic Usage with Default Structure
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# Default structure expects:
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# - train/good: Normal (good) training images
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# - test/good: Normal test images
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# - test/defect: Anomalous test images
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datamodule = Folder(
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name="my_dataset",
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root=Path("./datasets/my_dataset"),
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normal_dir="good", # Subfolder containing normal images
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abnormal_dir="defect", # Subfolder containing anomalous images
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)
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# 2. Custom Directory Structure
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# For a different directory structure:
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# my_dataset/
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# ├── train/
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# │ └── normal/ # Normal training images
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# ├── val/
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# │ ├── normal/ # Normal validation images
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# │ └── anomaly/ # Anomalous validation images
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# └── test/
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# ├── normal/ # Normal test images
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# └── anomaly/ # Anomalous test images
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datamodule = Folder(
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name="my_dataset",
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root=Path("./datasets/my_dataset"),
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normal_dir="normal", # Subfolder containing normal images
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abnormal_dir="anomaly", # Subfolder containing anomalous images
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train_batch_size=32,
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eval_batch_size=32,
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num_workers=8,
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)
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