Source code for

import os
import warnings
from tempfile import TemporaryDirectory as InTemporaryDirectory
from urllib.request import urlretrieve

import numpy as np
from PIL import Image

from fury.lib import (
from fury.utils import set_input

[docs] def load_cubemap_texture(fnames, interpolate_on=True, mipmap_on=True): """Load a cube map texture from a list of 6 images. Parameters ---------- fnames : list of strings List of 6 filenames with bmp, jpg, jpeg, png, tif or tiff extensions. interpolate_on : bool, optional mipmap_on : bool, optional Returns ------- output : vtkTexture Cube map texture. """ if len(fnames) != 6: raise IOError('Expected 6 filenames, got {}'.format(len(fnames))) texture = Texture() texture.CubeMapOn() for idx, fn in enumerate(fnames): if not os.path.isfile(fn): raise FileNotFoundError(fn) else: # Read the images vtk_img = load_image(fn, as_vtktype=True) # Flip the image horizontally img_flip = ImageFlip() img_flip.SetInputData(vtk_img) img_flip.SetFilteredAxis(1) # flip y axis img_flip.Update() # Add the image to the cube map texture.SetInputDataObject(idx, img_flip.GetOutput()) if interpolate_on: texture.InterpolateOn() if mipmap_on: texture.MipmapOn() return texture
[docs] def load_image(filename, as_vtktype=False, use_pillow=True): """Load an image. Parameters ---------- filename: str should be png, bmp, jpeg or jpg files as_vtktype: bool, optional if True, return vtk output otherwise an ndarray. Default False. use_pillow: bool, optional Use pillow python library to load the files. Default True Returns ------- image: ndarray or vtk output desired image array """ is_url = filename.lower().startswith('http://') or filename.lower().startswith( 'https://' ) if is_url: image_name = os.path.basename(filename) if len(image_name.split('.')) < 2: raise IOError(f'{filename} is not a valid image URL') urlretrieve(filename, image_name) filename = image_name if use_pillow: with as pil_image: if pil_image.mode in ['P']: pil_image = pil_image.convert('RGB') if pil_image.mode in ['RGBA', 'RGB', 'L']: image = np.asarray(pil_image) elif pil_image.mode.startswith('I;16'): raw = pil_image.tobytes('raw', pil_image.mode) dtype = '>u2' if pil_image.mode.endswith('B') else '<u2' image = np.frombuffer(raw, dtype=dtype) image.reshape(pil_image.size[::-1]).astype('=u2') else: try: image = pil_image.convert('RGBA') except ValueError: raise RuntimeError('Unknown image mode {}'.format(pil_image.mode)) image = np.asarray(pil_image) if as_vtktype: if image.ndim not in [2, 3]: raise IOError('only 2D (L, RGB, RGBA) or 3D image available') vtk_image = ImageData() depth = 1 if image.ndim == 2 else image.shape[2] # width, height vtk_image.SetDimensions(image.shape[1], image.shape[0], depth) vtk_image.SetExtent(0, image.shape[1] - 1, 0, image.shape[0] - 1, 0, 0) vtk_image.SetSpacing(1.0, 1.0, 1.0) vtk_image.SetOrigin(0.0, 0.0, 0.0) image = np.flipud(image) image = image.reshape(image.shape[1] * image.shape[0], depth) image = np.ascontiguousarray(image, dtype=image.dtype) vtk_array_type = numpy_support.get_vtk_array_type(image.dtype) uchar_array = numpy_support.numpy_to_vtk( image, deep=True, array_type=vtk_array_type ) vtk_image.GetPointData().SetScalars(uchar_array) image = vtk_image if is_url: os.remove(filename) return image d_reader = { '.png': PNGReader, '.bmp': BMPReader, '.jpeg': JPEGReader, '.jpg': JPEGReader, '.tiff': TIFFReader, '.tif': TIFFReader, } extension = os.path.splitext(os.path.basename(filename).lower())[1] if extension.lower() not in d_reader.keys(): raise IOError( 'Impossible to read the file {0}: Unknown extension {1}'.format( filename, extension ) ) reader = d_reader.get(extension)() reader.SetFileName(filename) reader.Update() reader.GetOutput().GetPointData().GetArray(0).SetName('original') if not as_vtktype: w, h, _ = reader.GetOutput().GetDimensions() vtk_array = reader.GetOutput().GetPointData().GetScalars() components = vtk_array.GetNumberOfComponents() image = numpy_support.vtk_to_numpy(vtk_array).reshape(h, w, components) image = np.flipud(image) if is_url: os.remove(filename) return reader.GetOutput() if as_vtktype else image
[docs] def load_text(file): """Load a text file. Parameters ---------- file: str Path to the text file. Returns ------- text: str Text contained in the file. """ if not os.path.isfile(file): raise IOError('File {} does not exist.'.format(file)) with open(file) as f: text = return text
[docs] def save_image( arr, filename, compression_quality=75, compression_type='deflation', use_pillow=True, dpi=(72, 72), ): """Save a 2d or 3d image. Expect an image with the following shape: (H, W) or (H, W, 1) or (H, W, 3) or (H, W, 4). Parameters ---------- arr : ndarray array to save filename : string should be png, bmp, jpeg or jpg files compression_quality : int, optional compression_quality for jpeg data. 0 = Low quality, 100 = High quality compression_type : str, optional compression type for tiff file select between: None, lzw, deflation (default) use_pillow : bool, optional Use imageio python library to save the files. dpi : float or (float, float) Dots per inch (dpi) for saved image. Single values are applied as dpi for both dimensions. """ if arr.ndim > 3: raise IOError('Image Dimensions should be <=3') if isinstance(dpi, (float, int)): dpi = (dpi, dpi) d_writer = { '.png': PNGWriter, '.bmp': BMPWriter, '.jpeg': JPEGWriter, '.jpg': JPEGWriter, '.tiff': TIFFWriter, '.tif': TIFFWriter, } extension = os.path.splitext(os.path.basename(filename).lower())[1] if extension.lower() not in d_writer.keys(): raise IOError( 'Impossible to save the file {0}: Unknown extension {1}'.format( filename, extension ) ) if use_pillow: im = Image.fromarray(arr), quality=compression_quality, dpi=dpi) else: warnings.warn(UserWarning('DPI value is ignored while saving images via vtk.')) if arr.ndim == 2: arr = arr[..., None] shape = arr.shape arr = np.flipud(arr) if extension.lower() in [ '.png', ]: arr = arr.astype(np.uint8) arr = arr.reshape((shape[1] * shape[0], shape[2])) arr = np.ascontiguousarray(arr, dtype=arr.dtype) vtk_array_type = numpy_support.get_vtk_array_type(arr.dtype) vtk_array = numpy_support.numpy_to_vtk( num_array=arr, deep=True, array_type=vtk_array_type ) # Todo, look the following link for managing png 16bit # vtk_data = ImageData() vtk_data.SetDimensions(shape[1], shape[0], shape[2]) vtk_data.SetExtent(0, shape[1] - 1, 0, shape[0] - 1, 0, 0) vtk_data.SetSpacing(1.0, 1.0, 1.0) vtk_data.SetOrigin(0.0, 0.0, 0.0) vtk_data.GetPointData().SetScalars(vtk_array) writer = d_writer.get(extension)() writer.SetFileName(filename) writer.SetInputData(vtk_data) if extension.lower() in ['.jpg', '.jpeg']: writer.ProgressiveOn() writer.SetQuality(compression_quality) if extension.lower() in ['.tif', '.tiff']: compression_type = compression_type or 'nocompression' l_compression = ['nocompression', 'packbits', 'jpeg', 'deflate', 'lzw'] if compression_type.lower() in l_compression: comp_id = l_compression.index(compression_type.lower()) writer.SetCompression(comp_id) else: writer.SetCompressionToDeflate() writer.Write()
[docs] def load_polydata(file_name): """Load a vtk polydata to a supported format file. Supported file formats are VTK, VTP, FIB, PLY, STL XML and OBJ Parameters ---------- file_name : string Returns ------- output : vtkPolyData """ # Check if file actually exists if not os.path.isfile(file_name): raise FileNotFoundError(file_name) file_extension = file_name.split('.')[-1].lower() poly_reader = { 'vtk': PolyDataReader, 'vtp': XMLPolyDataReader, 'fib': PolyDataReader, 'ply': PLYReader, 'stl': STLReader, 'xml': XMLPolyDataReader, } if file_extension in poly_reader.keys(): reader = poly_reader.get(file_extension)() elif file_extension == 'obj': # Special case, since there is two obj format reader = OBJReader() reader.SetFileName(file_name) reader.Update() if reader.GetOutput().GetNumberOfCells() == 0: reader = MNIObjectReader() else: raise IOError('.' + file_extension + ' is not supported by FURY') reader.SetFileName(file_name) reader.Update() return reader.GetOutput()
[docs] def save_polydata(polydata, file_name, binary=False, color_array_name=None): """Save a vtk polydata to a supported format file. Save formats can be VTK, FIB, PLY, STL and XML. Parameters ---------- polydata : vtkPolyData file_name : string binary : bool color_array_name: ndarray """ # get file extension (type) file_extension = file_name.split('.')[-1].lower() poly_writer = { 'vtk': PolyDataWriter, 'vtp': XMLPolyDataWriter, 'fib': PolyDataWriter, 'ply': PLYWriter, 'stl': STLWriter, 'xml': XMLPolyDataWriter, } if file_extension in poly_writer.keys(): writer = poly_writer.get(file_extension)() elif file_extension == 'obj': # Special case, since there is two obj format find_keyword = file_name.lower().split('.') if 'mni' in find_keyword or 'mnc' in find_keyword: writer = MNIObjectWriter() else: raise IOError( 'Wavefront obj requires a scene \n' " for MNI obj, use '.mni.obj' extension" ) else: raise IOError('.' + file_extension + ' is not supported by FURY') writer.SetFileName(file_name) writer = set_input(writer, polydata) if color_array_name is not None and file_extension == 'ply': writer.SetArrayName(color_array_name) if binary: writer.SetFileTypeToBinary() writer.Update() writer.Write()
[docs] def load_sprite_sheet(sheet_path, nb_rows, nb_cols, as_vtktype=False): """Process and load sprites from a sprite sheet. Parameters ---------- sheet_path: str Path to the sprite sheet nb_rows: int Number of rows in the sprite sheet nb_cols: int Number of columns in the sprite sheet as_vtktype: bool, optional If True, the output is a vtkImageData Returns ------- Dict containing the processed sprites. """ sprite_dicts = {} sprite_sheet = load_image(sheet_path) width, height = sprite_sheet.shape[:2] sprite_size_x = int(np.ceil(width / nb_rows)) sprite_size_y = int(np.ceil(height / nb_cols)) for row, col in np.ndindex((nb_rows, nb_cols)): nxt_row = row + 1 nxt_col = col + 1 box = ( row * sprite_size_x, col * sprite_size_y, nxt_row * sprite_size_x, nxt_col * sprite_size_y, ) sprite_arr = sprite_sheet[box[0] : box[2], box[1] : box[3]] if as_vtktype: with InTemporaryDirectory() as tdir: tmp_img_path = os.path.join(tdir, f'{row}{col}.png') save_image(sprite_arr, tmp_img_path, compression_quality=100) sprite_dicts[(row, col)] = load_image(tmp_img_path, as_vtktype=True) else: sprite_dicts[(row, col)] = sprite_arr return sprite_dicts