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dda5b2a367
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.
122 lines
4.3 KiB
Python
122 lines
4.3 KiB
Python
"""Tests for image visualization functions."""
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# Copyright (C) 2025 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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import pytest
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from PIL import Image
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from anomalib.visualization.image.functional import np_to_pil_image
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@pytest.fixture
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def rng() -> np.random.Generator:
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"""Create a random number generator."""
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return np.random.default_rng(42)
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class TestNumpyToPILImage:
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"""Test suite for np_to_pil_image function."""
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@staticmethod
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def test_grayscale_conversion(rng: np.random.Generator) -> None:
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"""Test converting grayscale numpy array to PIL Image."""
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# Test with 2D array
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array = rng.random((100, 100))
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image = np_to_pil_image(array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert image.size == (100, 100)
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assert np.array(image).max() <= 255
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assert np.array(image).min() >= 0
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# Test with boolean array
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bool_array = np.array([[True, False], [False, True]])
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image = np_to_pil_image(bool_array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert image.size == (2, 2)
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assert np.array(image).max() == 255
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assert np.array(image).min() == 0
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# Test with uint8 array
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uint8_array = np.array([[0, 128], [128, 255]], dtype=np.uint8)
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image = np_to_pil_image(uint8_array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert image.size == (2, 2)
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assert np.array(image).max() == 255
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assert np.array(image).min() == 0
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@staticmethod
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def test_rgb_conversion(rng: np.random.Generator) -> None:
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"""Test converting RGB numpy array to PIL Image."""
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# Test with 3D array (H, W, 3)
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array = rng.random((100, 100, 3))
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image = np_to_pil_image(array)
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assert isinstance(image, Image.Image)
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assert image.mode == "RGB"
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assert image.size == (100, 100)
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assert np.array(image).max() <= 255
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assert np.array(image).min() >= 0
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# Test with boolean RGB array
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bool_array = np.array([[[True, False, True], [False, True, False]]], dtype=bool)
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image = np_to_pil_image(bool_array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert np.array(image).max() == 255
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assert np.array(image).min() == 0
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# Test with uint8 RGB array
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uint8_array = np.array([[[0, 128, 255], [255, 128, 0]]], dtype=np.uint8)
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image = np_to_pil_image(uint8_array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert np.array(image).max() == 255
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assert np.array(image).min() == 0
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@staticmethod
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def test_singleton_dimensions(rng: np.random.Generator) -> None:
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"""Test handling of arrays with singleton dimensions."""
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# Test with (1, H, W) array
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array = rng.random((1, 100, 100))
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image = np_to_pil_image(array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert image.size == (100, 100)
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assert np.array(image).max() <= 255
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assert np.array(image).min() >= 0
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# Test with (H, W, 1) array
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array = rng.random((100, 100, 1))
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image = np_to_pil_image(array)
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assert isinstance(image, Image.Image)
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assert image.mode == "L"
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assert image.size == (100, 100)
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assert np.array(image).max() <= 255
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assert np.array(image).min() >= 0
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# Test with (1, H, W, 3) array
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array = rng.random((1, 100, 100, 3))
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image = np_to_pil_image(array)
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assert isinstance(image, Image.Image)
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assert image.mode == "RGB"
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assert image.size == (100, 100)
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assert np.array(image).max() <= 255
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assert np.array(image).min() >= 0
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@staticmethod
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def test_invalid_dimensions(rng: np.random.Generator) -> None:
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"""Test handling of arrays with invalid dimensions."""
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# Test with 1D array
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array = rng.random(100)
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with pytest.raises(ValueError, match="Expected 2D array"):
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np_to_pil_image(array)
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# Test with 3D array that's not RGB
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array = rng.random((100, 100, 4))
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with pytest.raises(ValueError, match="Expected 2D array"):
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np_to_pil_image(array)
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