mirror of
https://github.com/python-pillow/Pillow.git
synced 2025-08-09 14:54:46 +03:00
Rework handling of awkward image modes and rescaling
Expose Image.use_display_hook_features that can be used to control how
images are seen in IPython / Jupyter. For example:
Image.use_display_hook_features(F_mode='unit')
special cases F mode images, by assuming values are in [0., 1.].
Alternatively, the user could do:
Image.use_display_hook_features('auto')
and it will function similarly to my previous patch.
This commit is contained in:
Sam Mason
parent
8bdb6553a4
commit
f6433362cd
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@ -138,50 +138,52 @@ class TestImage:
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assert_image_equal(im, im2, 17)
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# make sure higher bit depths get converted down to 8BPC with warnings
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high = Image.new("I;16", (100, 100))
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with pytest.warns(UserWarning):
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bundle = high._repr_mimebundle_()
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high = Image.new("I;16", (100, 100), 65535)
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bundle = high._repr_mimebundle_()
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert im2.format == "PNG"
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assert_image_equal(im, im2)
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assert_image_equal(high.convert("I"), im2)
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high = Image.new("F", (100, 100))
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with pytest.warns(UserWarning):
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bundle = high._repr_mimebundle_()
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert im2.format == "PNG"
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assert_image_equal(im, im2)
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bundle = high._repr_mimebundle_()
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assert bundle["image/jpeg"] is None and bundle["image/png"] is None
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high = Image.new("I", (100, 100))
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with pytest.warns(UserWarning):
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bundle = high._repr_mimebundle_()
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bundle = high._repr_mimebundle_()
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert im2.format == "PNG"
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assert_image_equal(im, im2)
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assert_image_equal(high, im2)
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# make sure large image gets scaled down with a warning
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im = Image.new("L", [3000, 3000])
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with pytest.warns(UserWarning):
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bundle = im._repr_mimebundle_()
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def test_repr_mimebundle_hooks(self):
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previous = Image._to_ipython_image
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try:
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Image.use_display_hook_features("auto")
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert im2.size == (1500, 1500)
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assert_image_equal(im.resize(im2.size), im2)
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# fmake sure large image gets scaled down with a warning
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im = Image.new("L", [3000, 3000])
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with pytest.warns(UserWarning):
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bundle = im._repr_mimebundle_()
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# make sure common modes get converted without a warning
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im = Image.new("LAB", (100, 100))
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with pytest.warns(None) as record:
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bundle = im._repr_mimebundle_()
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assert len(record) == 0
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert_image_equal(im.convert("RGB"), im2)
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert im2.size == (1500, 1500)
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assert_image_equal(im.resize(im2.size), im2)
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im = Image.new("HSV", (100, 100))
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with pytest.warns(None) as record:
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bundle = im._repr_mimebundle_()
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assert len(record) == 0
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert_image_equal(im.convert("RGB"), im2)
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# make sure common modes get converted without a warning
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im = Image.new("LAB", (100, 100))
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with pytest.warns(None) as record:
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bundle = im._repr_mimebundle_()
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assert len(record) == 0
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert_image_equal(im.convert("RGB"), im2)
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im = Image.new("HSV", (100, 100))
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with pytest.warns(None) as record:
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bundle = im._repr_mimebundle_()
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assert len(record) == 0
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with Image.open(io.BytesIO(bundle["image/png"])) as im2:
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assert_image_equal(im.convert("RGB"), im2)
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finally:
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Image._to_ipython_image = previous
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def test_open_formats(self):
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PNGFILE = "Tests/images/hopper.png"
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162
src/PIL/Image.py
162
src/PIL/Image.py
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@ -471,41 +471,157 @@ _IPYTHON_MODE_MAP = {
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_VALID_MODES_FOR_FORMAT = {
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"JPEG": {"L", "RGB", "YCbCr", "CMYK"},
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"PNG": {"1", "P", "L", "RGB", "RGBA", "LA", "PA"},
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"PNG": {"1", "P", "L", "RGB", "RGBA", "LA", "PA", "I", "I;16"},
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}
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def _to_ipython_image(image):
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"""Simplify image to something suitable for display in IPython/Jupyter.
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Notably, convert to 8BPC and rescale by some integer factor.
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"""Transform image to something suitable for display in IPython/Jupyter.
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See use_display_hook_features.
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"""
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if image.mode in {"I", "F"}:
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warnings.warn(
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"image mode doesn't have well defined min/max value, using extrema"
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)
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return image
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def use_display_hook_features(
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default=None,
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*,
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I_mode=None,
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F_mode=None,
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I16_mode=None,
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resize_threshold=None,
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mode_map=None,
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):
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"""Set IPython/Jupyter display hook up based on parameters.
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:param default: setting to use when unspecified
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:param I_mode: what to do with I mode images
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:param F_mode: what to do with F mode images
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:param I16_mode: what to do with F mode images
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:param resize_threshold: images with width or height much
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larger than this will be resized
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:param mode_map: a dictionary like _IPYTHON_MODE_MAP
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when modes are set luminance values will be linearly rescaled such that;
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'extrema': darkest value to black, brightest to white
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'scale max': 0 value to black, brightest to white
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'unit': 0 to black, 1 to white
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'assume i16': 0 to black, 2^16-1 to white
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'assume i32': 0 to black, 2^32-1 to white
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All parameters can be specified as 'auto', which will cause the following
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settings to be used:
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I_mode, F_mode = 'scale_max'
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I16_mode = 'assume i16'
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resize_threshold = IPYTHON_RESIZE_THRESHOLD
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mode_map = _IPYTHON_MODE_MAP
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"""
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def identity(image):
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"leave the image as is"
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return image
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def extrema_to_L(image):
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# linearly transform extrema to fit in [0, 255]
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# this should have a similar result as Image.histogram
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lo, hi = image.getextrema()
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scale = 256 / (hi - lo) if lo != hi else 1
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image = image.point(lambda e: (e - lo) * scale).convert("L")
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elif image.mode == "I;16":
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warnings.warn("converting 16BPC image to 8BPC for display in IPython/Jupyter")
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# linearly transform max down to 255
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image = image.point(lambda e: e / 256).convert("L")
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# shrink large images so they don't take too long to transfer/render
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factor = max(image.size) // IPYTHON_RESIZE_THRESHOLD
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if factor > 1:
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warnings.warn(
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"scaling large image down to improve performance in IPython/Jupyter"
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f"converting image to 8BPC using black={lo}, white={hi} for display"
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)
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image = image.reduce(factor)
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scale = 256 / (hi - lo) if lo != hi else 1
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return image.point(lambda e: (e - lo) * scale).convert("L")
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# process remaining modes into things supported by writers
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if image.mode in _IPYTHON_MODE_MAP:
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image = image.convert(_IPYTHON_MODE_MAP[image.mode])
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def scale_max_to_L(image):
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_, hi = image.getextrema()
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warnings.warn(f"converting image to 8BPC using black=0, white={hi} for display")
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if hi > 0:
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scale = 256 / hi
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return image.point(lambda e: e * scale).convert("L")
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return image
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return image
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def unit_to_L(image):
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warnings.warn("converting 8BPC for display, with range [0, 1]")
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return image.point(lambda e: e * 255).convert("L")
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def I16_to_L(image):
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warnings.warn("converting 16BPC image to 8BPC for display")
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# linearly transform max down to 255
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return image.point(lambda e: e / 256).convert("L")
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def I32_to_L(image):
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warnings.warn("converting 32BPC image to 8BPC for display")
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return image.point(lambda e: e / 2**24).convert("L")
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def hook_for_mode(value, auto):
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if value is None:
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return identity
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if value in "auto":
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return auto
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if value == "extrema":
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return extrema_to_L
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if value == "scale max":
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return scale_max_to_L
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if value == "unit":
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return unit_to_L
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if value == "assume i16":
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return I16_to_L
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if value == "assume i32":
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return I32_to_L
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assert isinstance(value, Callable)
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return value
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def threshold_resize(image):
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# smaller images are quicker to process
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factor = max(image.size) // resize_threshold
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if factor > 1:
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warnings.warn(
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"scaling large image down to improve performance in IPython/Jupyter"
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)
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return image.reduce(factor)
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return image
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# decode arguments
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handle_I = hook_for_mode(I_mode or default, scale_max_to_L)
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handle_F = hook_for_mode(F_mode or default, scale_max_to_L)
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handle_I16 = hook_for_mode(I16_mode or default, I16_to_L)
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resize_threshold = resize_threshold or default
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if resize_threshold is None:
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resize_image = identity
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else:
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if resize_threshold == "auto":
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resize_threshold = IPYTHON_RESIZE_THRESHOLD
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assert isinstance(resize_threshold, int)
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resize_image = threshold_resize
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mode_map = mode_map or default
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if mode_map == "auto":
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mode_map = _IPYTHON_MODE_MAP
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elif mode_map is None:
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mode_map = {}
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else:
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assert isinstance(mode_map, dict)
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# define our hook
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def fn(image):
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if image.mode == "I":
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image = handle_I(image)
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elif image.mode == "F":
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image = handle_F(image)
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elif image.mode == "I;16":
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image = handle_I16(image)
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image = resize_image(image)
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# process remaining modes into things supported by writers
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if image.mode in mode_map:
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image = image.convert(mode_map[image.mode])
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return image
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# install it
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global _to_ipython_image
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_to_ipython_image = fn
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def _encode_ipython_image(image, image_format):
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