def test_skybox():
# Test scene created without skybox
scene = window.Scene()
npt.assert_warns(UserWarning, scene.skybox)
# Test removing automatically shown skybox
test_tex = Texture()
test_tex.CubeMapOn()
checker_arr = np.array([[1, 0], [0, 1]], dtype=np.uint8) * 255
for i in range(6):
vtk_img = ImageData()
vtk_img.SetDimensions(2, 2, 1)
img_arr = np.zeros((2, 2, 3), dtype=np.uint8)
img_arr[:, :, i // 2] = checker_arr
vtk_arr = numpy_support.numpy_to_vtk(img_arr.reshape((-1, 3),
order='F'))
vtk_arr.SetName('Image')
img_point_data = vtk_img.GetPointData()
img_point_data.AddArray(vtk_arr)
img_point_data.SetActiveScalars('Image')
test_tex.SetInputDataObject(i, vtk_img)
scene = window.Scene(skybox=test_tex)
report = window.analyze_scene(scene)
npt.assert_equal(report.actors, 1)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [0, 0, 255])
npt.assert_array_equal(ss[75, 225, :], [0, 0, 0])
scene.yaw(90)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [255, 0, 0])
npt.assert_array_equal(ss[75, 225, :], [0, 0, 0])
scene.pitch(90)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [0, 0, 0])
npt.assert_array_equal(ss[75, 225, :], [0, 255, 0])
# Test skybox is not added twice
scene.skybox()
report = window.analyze_scene(scene)
npt.assert_equal(report.actors, 1)
# Test make skybox invisible
scene.skybox(visible=False)
report = window.analyze_scene(scene)
npt.assert_equal(report.actors, 0)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [0, 0, 0])
scene.yaw(90)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [0, 0, 0])
scene.pitch(90)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 225, :], [0, 0, 0])
# Test make skybox visible again
scene.skybox(visible=True)
report = window.analyze_scene(scene)
npt.assert_equal(report.actors, 1)
def numpy_to_vtk_image_data(array,
spacing=(1.0, 1.0, 1.0),
origin=(0.0, 0.0, 0.0),
deep=True):
"""Convert numpy array to a vtk image data.
Parameters
----------
array : ndarray
pixel coordinate and colors values.
spacing : (float, float, float) (optional)
sets the size of voxel (unit of space in each direction x,y,z)
origin : (float, float, float) (optional)
sets the origin at the given point
deep : bool (optional)
decides the type of copy(ie. deep or shallow)
Returns
-------
vtk_image : vtkImageData
"""
if array.ndim not in [2, 3]:
raise IOError("only 2D (L, RGB, RGBA) or 3D image available")
vtk_image = ImageData()
depth = 1 if array.ndim == 2 else array.shape[2]
vtk_image.SetDimensions(array.shape[1], array.shape[0], depth)
vtk_image.SetExtent(0, array.shape[1] - 1, 0, array.shape[0] - 1, 0, 0)
vtk_image.SetSpacing(spacing)
vtk_image.SetOrigin(origin)
temp_arr = np.flipud(array)
temp_arr = temp_arr.reshape(array.shape[1] * array.shape[0], depth)
temp_arr = np.ascontiguousarray(temp_arr, dtype=array.dtype)
vtk_array_type = numpy_support.get_vtk_array_type(array.dtype)
uchar_array = numpy_support.numpy_to_vtk(temp_arr,
deep=deep,
array_type=vtk_array_type)
vtk_image.GetPointData().SetScalars(uchar_array)
return vtk_image
def rgb_to_vtk(data):
"""RGB or RGBA images to VTK arrays.
Parameters
----------
data : ndarray
Shape can be (X, Y, 3) or (X, Y, 4)
Returns
-------
vtkImageData
"""
grid = ImageData()
grid.SetDimensions(data.shape[1], data.shape[0], 1)
nd = data.shape[-1]
vtkarr = numpy_support.numpy_to_vtk(
np.flip(data.swapaxes(0, 1), axis=1).reshape((-1, nd), order='F'))
vtkarr.SetName('Image')
grid.GetPointData().AddArray(vtkarr)
grid.GetPointData().SetActiveScalars('Image')
grid.GetPointData().Update()
return grid
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 Image.open(filename) as pil_image:
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)
image = np.flipud(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 = 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)
if is_url:
os.remove(filename)
return reader.GetOutput() if as_vtktype else image
def save_image(arr,
filename,
compression_quality=75,
compression_type='deflation',
use_pillow=True):
"""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.
"""
if arr.ndim > 3:
raise IOError("Image Dimensions should be <=3")
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:
arr = np.flipud(arr)
im = Image.fromarray(arr)
im.save(filename, quality=compression_quality)
return
if arr.ndim == 2:
arr = arr[..., None]
shape = arr.shape
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
# https://stackoverflow.com/questions/15667947/vtkpngwriter-printing-out-black-images
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()
def test_scene():
scene = window.Scene()
# Scene size test
npt.assert_equal(scene.size(), (0, 0))
# Color background test
# Background color for scene (1, 0.5, 0). 0.001 added here to remove
# numerical errors when moving from float to int values
bg_float = (1, 0.501, 0)
# That will come in the image in the 0-255 uint scale
bg_color = tuple((np.round(255 * np.array(bg_float))).astype('uint8'))
scene.background(bg_float)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr, bg_color=bg_color,
colors=[bg_color, (0, 127, 0)])
npt.assert_equal(report.objects, 0)
npt.assert_equal(report.colors_found, [True, False])
# Add actor to scene to test the remove actor function by analyzing a
# snapshot
axes = actor.axes()
scene.add(axes)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr, bg_color)
npt.assert_equal(report.objects, 1)
# Test remove actor function by analyzing a snapshot
scene.rm(axes)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr, bg_color)
npt.assert_equal(report.objects, 0)
# Add actor to scene to test the remove all actors function by analyzing a
# snapshot
scene.add(axes)
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr, bg_color)
npt.assert_equal(report.objects, 1)
# Test remove all actors function by analyzing a snapshot
scene.rm_all()
arr = window.snapshot(scene)
report = window.analyze_snapshot(arr, bg_color)
npt.assert_equal(report.objects, 0)
# Test change background color from scene by analyzing the scene
ren2 = window.Scene(bg_float)
ren2.background((0, 0, 0.))
report = window.analyze_scene(ren2)
npt.assert_equal(report.bg_color, (0, 0, 0))
# Add actor to scene to test the remove actor function by analyzing the
# scene
ren2.add(axes)
report = window.analyze_scene(ren2)
npt.assert_equal(report.actors, 1)
# Test remove actor function by analyzing the scene
ren2.rm(axes)
report = window.analyze_scene(ren2)
npt.assert_equal(report.actors, 0)
# Test camera information retrieving
with captured_output() as (out, err):
scene.camera_info()
npt.assert_equal(out.getvalue().strip(),
'# Active Camera\n '
'Position (0.00, 0.00, 1.00)\n '
'Focal Point (0.00, 0.00, 0.00)\n '
'View Up (0.00, 1.00, 0.00)')
npt.assert_equal(err.getvalue().strip(), '')
# Test skybox
scene = window.Scene()
npt.assert_equal(scene.GetUseImageBasedLighting(), False)
npt.assert_equal(scene.GetAutomaticLightCreation(), 1)
npt.assert_equal(scene.GetSphericalHarmonics(), None)
npt.assert_equal(scene.GetEnvironmentTexture(), None)
test_tex = Texture()
scene = window.Scene(skybox=test_tex)
npt.assert_equal(scene.GetUseImageBasedLighting(), True)
npt.assert_equal(scene.GetAutomaticLightCreation(), 0)
npt.assert_equal(scene.GetSphericalHarmonics(), None)
npt.assert_equal(scene.GetEnvironmentTexture(), test_tex)
# Test automatically shown skybox
test_tex = Texture()
test_tex.CubeMapOn()
checker_arr = np.array([[1, 0], [0, 1]], dtype=np.uint8) * 255
for i in range(6):
vtk_img = ImageData()
vtk_img.SetDimensions(2, 2, 1)
img_arr = np.zeros((2, 2, 3), dtype=np.uint8)
img_arr[:, :, i // 2] = checker_arr
vtk_arr = numpy_support.numpy_to_vtk(img_arr.reshape((-1, 3),
order='F'))
vtk_arr.SetName('Image')
img_point_data = vtk_img.GetPointData()
img_point_data.AddArray(vtk_arr)
img_point_data.SetActiveScalars('Image')
test_tex.SetInputDataObject(i, vtk_img)
scene = window.Scene(skybox=test_tex)
report = window.analyze_scene(scene)
npt.assert_equal(report.actors, 1)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [0, 0, 255])
npt.assert_array_equal(ss[75, 225, :], [0, 0, 0])
scene.yaw(90)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [255, 0, 0])
npt.assert_array_equal(ss[75, 225, :], [0, 0, 0])
scene.pitch(90)
ss = window.snapshot(scene)
npt.assert_array_equal(ss[75, 75, :], [0, 0, 0])
npt.assert_array_equal(ss[75, 225, :], [0, 255, 0])