Download envs/kitoverlay/skimage/io/_plugins/pil_plugin.py from AVSim/simulation-package: direct link, hf CLI and curl.
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https://huggingface.co/datasets/AVSim/simulation-package/resolve/main/envs/kitoverlay/skimage/io/_plugins/pil_plugin.py
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7.78 kB
| __all__ = ['imread', 'imsave'] | |
| import numpy as np | |
| from PIL import Image | |
| from ...util import img_as_ubyte, img_as_uint | |
| def imread(fname, dtype=None, img_num=None, **kwargs): | |
| """Load an image from file. | |
| Parameters | |
| ---------- | |
| fname : str or file | |
| File name or file-like-object. | |
| dtype : numpy dtype object or string specifier | |
| Specifies data type of array elements. | |
| img_num : int, optional | |
| Specifies which image to read in a file with multiple images | |
| (zero-indexed). | |
| kwargs : keyword pairs, optional | |
| Addition keyword arguments to pass through. | |
| Notes | |
| ----- | |
| Files are read using the Python Imaging Library. | |
| See PIL docs [1]_ for a list of supported formats. | |
| References | |
| ---------- | |
| .. [1] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html | |
| """ | |
| if isinstance(fname, str): | |
| with open(fname, 'rb') as f: | |
| im = Image.open(f) | |
| return pil_to_ndarray(im, dtype=dtype, img_num=img_num) | |
| else: | |
| im = Image.open(fname) | |
| return pil_to_ndarray(im, dtype=dtype, img_num=img_num) | |
| def pil_to_ndarray(image, dtype=None, img_num=None): | |
| """Import a PIL Image object to an ndarray, in memory. | |
| Parameters | |
| ---------- | |
| Refer to ``imread``. | |
| """ | |
| try: | |
| # this will raise an IOError if the file is not readable | |
| image.getdata()[0] | |
| except OSError as e: | |
| site = "http://pillow.readthedocs.org/en/latest/installation.html#external-libraries" | |
| pillow_error_message = str(e) | |
| error_message = ( | |
| f"Could not load '{image.filename}' \n" | |
| f"Reason: '{pillow_error_message}'\n" | |
| f"Please see documentation at: {site}" | |
| ) | |
| raise ValueError(error_message) | |
| frames = [] | |
| grayscale = None | |
| i = 0 | |
| while 1: | |
| try: | |
| image.seek(i) | |
| except EOFError: | |
| break | |
| frame = image | |
| if img_num is not None and img_num != i: | |
| image.getdata()[0] | |
| i += 1 | |
| continue | |
| if image.format == 'PNG' and image.mode == 'I' and dtype is None: | |
| dtype = 'uint16' | |
| if image.mode == 'P': | |
| if grayscale is None: | |
| grayscale = _palette_is_grayscale(image) | |
| if grayscale: | |
| frame = image.convert('L') | |
| else: | |
| if image.format == 'PNG' and 'transparency' in image.info: | |
| frame = image.convert('RGBA') | |
| else: | |
| frame = image.convert('RGB') | |
| elif image.mode == '1': | |
| frame = image.convert('L') | |
| elif 'A' in image.mode: | |
| frame = image.convert('RGBA') | |
| elif image.mode == 'CMYK': | |
| frame = image.convert('RGB') | |
| if image.mode.startswith('I;16'): | |
| shape = image.size | |
| dtype = '>u2' if image.mode.endswith('B') else '<u2' | |
| if 'S' in image.mode: | |
| dtype = dtype.replace('u', 'i') | |
| frame = np.frombuffer(frame.tobytes(), dtype) | |
| frame.shape = shape[::-1] | |
| else: | |
| frame = np.array(frame, dtype=dtype) | |
| frames.append(frame) | |
| i += 1 | |
| if img_num is not None: | |
| break | |
| if hasattr(image, 'fp') and image.fp: | |
| image.fp.close() | |
| if img_num is None and len(frames) > 1: | |
| return np.array(frames) | |
| elif frames: | |
| return frames[0] | |
| elif img_num: | |
| raise IndexError(f'Could not find image #{img_num}') | |
| def _palette_is_grayscale(pil_image): | |
| """Return True if PIL image in palette mode is grayscale. | |
| Parameters | |
| ---------- | |
| pil_image : PIL image | |
| PIL Image that is in Palette mode. | |
| Returns | |
| ------- | |
| is_grayscale : bool | |
| True if all colors in image palette are gray. | |
| """ | |
| if pil_image.mode != 'P': | |
| raise ValueError('pil_image.mode must be equal to "P".') | |
| # get palette as an array with R, G, B columns | |
| # Starting in pillow 9.1 palettes may have less than 256 entries | |
| palette = np.asarray(pil_image.getpalette()).reshape((-1, 3)) | |
| # Not all palette colors are used; unused colors have junk values. | |
| start, stop = pil_image.getextrema() | |
| valid_palette = palette[start : stop + 1] | |
| # Image is grayscale if channel differences (R - G and G - B) | |
| # are all zero. | |
| return np.allclose(np.diff(valid_palette), 0) | |
| def ndarray_to_pil(arr, format_str=None): | |
| """Export an ndarray to a PIL object. | |
| Parameters | |
| ---------- | |
| Refer to ``imsave``. | |
| """ | |
| if arr.ndim == 3: | |
| arr = img_as_ubyte(arr) | |
| mode = {3: 'RGB', 4: 'RGBA'}[arr.shape[2]] | |
| elif format_str in ['png', 'PNG']: | |
| mode = 'I;16' | |
| if arr.dtype.kind == 'f': | |
| arr = img_as_uint(arr) | |
| elif arr.max() < 256 and arr.min() >= 0: | |
| arr = arr.astype(np.uint8) | |
| mode = 'L' | |
| else: | |
| arr = img_as_uint(arr) | |
| else: | |
| arr = img_as_ubyte(arr) | |
| mode = 'L' | |
| try: | |
| array_buffer = arr.tobytes() | |
| except AttributeError: | |
| array_buffer = arr.tostring() # Numpy < 1.9 | |
| if arr.ndim == 2: | |
| im = Image.new(mode, arr.T.shape) | |
| try: | |
| im.frombytes(array_buffer, 'raw', mode) | |
| except AttributeError: | |
| im.fromstring(array_buffer, 'raw', mode) # PIL 1.1.7 | |
| else: | |
| image_shape = (arr.shape[1], arr.shape[0]) | |
| try: | |
| im = Image.frombytes(mode, image_shape, array_buffer) | |
| except AttributeError: | |
| im = Image.fromstring(mode, image_shape, array_buffer) # PIL 1.1.7 | |
| return im | |
| def imsave(fname, arr, format_str=None, **kwargs): | |
| """Save an image to disk. | |
| Parameters | |
| ---------- | |
| fname : str or file-like object | |
| Name of destination file. | |
| arr : ndarray of uint8 or float | |
| Array (image) to save. Arrays of data-type uint8 should have | |
| values in [0, 255], whereas floating-point arrays must be | |
| in [0, 1]. | |
| format_str : str | |
| Format to save as, this is defaulted to PNG if using a file-like | |
| object; this will be derived from the extension if fname is a string | |
| kwargs : dict | |
| Keyword arguments to the Pillow save function (or tifffile save | |
| function, for Tiff files). These are format dependent. For example, | |
| Pillow's JPEG save function supports an integer ``quality`` argument | |
| with values in [1, 95], while TIFFFile supports a ``compress`` | |
| integer argument with values in [0, 9]. | |
| Notes | |
| ----- | |
| Use the Python Imaging Library. | |
| See PIL docs [1]_ for a list of other supported formats. | |
| All images besides single channel PNGs are converted using `img_as_uint8`. | |
| Single Channel PNGs have the following behavior: | |
| - Integer values in [0, 255] and Boolean types -> img_as_uint8 | |
| - Floating point and other integers -> img_as_uint16 | |
| References | |
| ---------- | |
| .. [1] http://pillow.readthedocs.org/en/latest/handbook/image-file-formats.html | |
| """ | |
| # default to PNG if file-like object | |
| if not isinstance(fname, str) and format_str is None: | |
| format_str = "PNG" | |
| # Check for png in filename | |
| if isinstance(fname, str) and fname.lower().endswith(".png"): | |
| format_str = "PNG" | |
| arr = np.asanyarray(arr) | |
| if arr.dtype.kind == 'b': | |
| arr = arr.astype(np.uint8) | |
| if arr.ndim not in (2, 3): | |
| raise ValueError(f"Invalid shape for image array: {arr.shape}") | |
| if arr.ndim == 3: | |
| if arr.shape[2] not in (3, 4): | |
| raise ValueError("Invalid number of channels in image array.") | |
| img = ndarray_to_pil(arr, format_str=format_str) | |
| img.save(fname, format=format_str, **kwargs) | |