__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 ' 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' mode_base = 'I' if arr.dtype.kind == 'f': arr = img_as_uint(arr) elif arr.max() < 256 and arr.min() >= 0: arr = arr.astype(np.uint8) mode = mode_base = 'L' else: arr = img_as_uint(arr) else: arr = img_as_ubyte(arr) mode = 'L' mode_base = 'L' try: array_buffer = arr.tobytes() except AttributeError: array_buffer = arr.tostring() # Numpy < 1.9 if arr.ndim == 2: im = Image.new(mode_base, 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)