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Fix PIL image conversion for uint16 multi-channel arrays. #11186

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Merged
copybara-service merged 1 commit into from
May 7, 2026
Merged

Fix PIL image conversion for uint16 multi-channel arrays. #11186

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15 changes: 12 additions & 3 deletions tensorflow_datasets/core/utils/image_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -177,16 +177,25 @@ def create_thumbnail(
if use_colormap: # Apply the colormap first as it modify the shape/dtype
ex = apply_colormap(ex)

_, _, c = ex.shape
c = ex.shape[-1] if ex.ndim == 3 else 1
postprocess = _postprocess_noop
if c == 1:
ex = ex.squeeze(axis=-1)
mode = 'L'
if ex.dtype == np.uint16:
mode = 'I;16'
postprocess = _postprocess_convert_rgb
else:
mode = 'L'
elif ex.dtype == np.uint16:
mode = 'I;16'
# PIL.Image.fromarray doesn't support uint16 for >1 channels.
# https://github.com/python-pillow/Pillow/blob/11.0.0/src/PIL/Image.py#L3225
# Scale to 8-bit for visualization.
ex = (ex / 257).astype(np.uint8)
mode = None
postprocess = _postprocess_convert_rgb
else:
mode = None
postprocess = _postprocess_convert_rgb
img = PIL_Image.fromarray(ex, mode=mode)
img = postprocess(img)
if default_dimensions:
Expand Down
22 changes: 22 additions & 0 deletions tensorflow_datasets/core/utils/image_utils_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@
import os

import numpy as np
import pytest
import tensorflow as tf
from tensorflow_datasets import testing
from tensorflow_datasets.core.utils import image_utils
Expand Down Expand Up @@ -94,5 +95,26 @@ def test_apply_colormap(self):
)


@pytest.mark.parametrize(
'dtype,fill_value,expected_mode,channels,expected_shape',
[
(np.uint8, 255, 'L', 1, (32, 32)),
(np.uint8, 255, 'RGB', 3, (32, 32, 3)),
(np.uint16, 65535, 'RGB', 1, (32, 32, 3)),
(np.uint16, 65535, 'RGB', 3, (32, 32, 3)),
],
)
def test_create_thumbnail_conversion(
dtype, fill_value, expected_mode, channels, expected_shape
):
img = np.full((32, 32, channels), fill_value=fill_value, dtype=dtype)
thumbnail = image_utils.create_thumbnail(
img, use_colormap=False, default_dimensions=True
)
assert thumbnail.mode == expected_mode
expected_array = np.full(expected_shape, fill_value=255, dtype=np.uint8)
np.testing.assert_array_equal(np.asarray(thumbnail), expected_array)


if __name__ == '__main__':
testing.test_main()
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