def __init__(self, viewer: LayeredImageViewer, config: UnitedConfig):
super().__init__(viewer, config)
self.mode = Mode.SHOW
self.radius = DEFAULT_RADIUS
self.paint_central_pixel_cluster = True
self.paint_dark_cluster = False
self.paint_connected_component = True
layers_properties = self.config.value('layers')
self.mask_palette = Palette.from_names_rows_dict(
layers_properties['mask']['palette'])
self.mask_background_class = self.mask_palette.row_index_by_name(
'background')
self.mask_foreground_class = self.mask_palette.row_index_by_name(
'foreground')
self.tool_mask_palette = Palette.from_names_rows_dict(
layers_properties['tool_mask']['palette'])
self.tool_background_class = self.tool_mask_palette.row_index_by_name(
'background')
self.tool_foreground_class = self.tool_mask_palette.row_index_by_name(
'foreground')
self.tool_eraser_class = self.tool_mask_palette.row_index_by_name(
'eraser')
self.tool_unconnected_component_class = self.tool_mask_palette.row_index_by_name(
'unconnected_component')
def create_colored_image_1(self):
active_sub_window = self.mdi.activeSubWindow()
if not isinstance(active_sub_window, LayeredImageViewerSubWindow):
return
layered_image = active_sub_window.viewer.data
layered_image.print_layers()
image = layered_image.layer_by_name('series').image
print('stat', image.array.shape, image.array.min(), image.array.max(),
image.array.dtype)
print(np.unique(image.array))
norm = (image.array / image.array.max() * 255).astype(np.uint8)
print('norm stat', norm.shape, norm.min(), norm.max(), norm.dtype)
import colorsys
palette_array = np.zeros((256, 4), dtype=np.uint8)
for i in range(256):
print('hsv', i, 60, 80)
hsv_decimal = (i / 360, 60 / 100, 80 / 100)
rgb_decimal = colorsys.hsv_to_rgb(*hsv_decimal)
rgb = tuple(round(i * 255) for i in rgb_decimal)
palette_array[i] = [*rgb, 255]
print('res conv', palette_array[i])
palette = Palette(palette_array)
indexed_image = VolumeImage(norm, palette, spatial=image.spatial)
layered_image.add_layer_from_image(indexed_image, 'colored')
def show_chart(self):
color_transfer_function = ColorTransferFunction()
color_transfer_function.add_point_from_x_color(
0, np.array([255, 0, 0, 255]))
color_transfer_function.add_point_from_x_color(
5, np.array([0, 255, 0, 50]))
color_transfer_function.add_point_from_x_color(
15, np.array([0, 255, 0, 255]))
color_transfer_function.add_point_from_x_color(
20, np.array([0, 0, 255, 255]))
self.w = ColorTransferFunctionViewer(color_transfer_function)
self.w.show()
self.w.setGeometry(800, 500, 900, 300)
# Create Palette from ColorTransferFunction
from scipy import interpolate
xp = [point.x for point in color_transfer_function.points]
fp = [point.color_array for point in color_transfer_function.points]
interpolator = interpolate.interp1d(xp, fp, axis=0, assume_sorted=True)
result = interpolator(np.linspace(0, 20))
print('res', result.shape, '\n', result)
palette_array = np.array(result.round(), dtype=np.uint8)
print('rounded', palette_array)
palette = Palette(palette_array)
def create_colored_image(self):
active_sub_window = self.mdi.activeSubWindow()
if not isinstance(active_sub_window, LayeredImageViewerSubWindow):
return
layered_image = active_sub_window.viewer.data
layered_image.print_layers()
image = layered_image.layer_by_name('series').image
print('stat', image.array.shape, image.array.min(), image.array.max(),
image.array.dtype)
print(np.unique(image.array))
discrete_color_len = 2000
norm = (image.array / image.array.max() *
(discrete_color_len - 1)).astype(np.int)
print('norm stat', norm.shape, norm.min(), norm.max(), norm.dtype)
color_transfer_function = ColorTransferFunction()
# color_transfer_function.add_point_from_x_color(0, np.array([255, 76, 76, 255]))
color_transfer_function.add_point_from_x_color(
0, np.array([0, 0, 0, 255]))
color_transfer_function.add_point_from_x_color(
0.128 * discrete_color_len, np.array([255, 211, 98, 255]))
color_transfer_function.add_point_from_x_color(
0.16 * discrete_color_len, np.array([152, 255, 108, 255]))
color_transfer_function.add_point_from_x_color(
0.20 * discrete_color_len, np.array([8, 255, 144, 255]))
color_transfer_function.add_point_from_x_color(
0.23 * discrete_color_len, np.array([221, 235, 255, 255]))
color_transfer_function.add_point_from_x_color(
0.25 * discrete_color_len, np.array([119, 196, 255, 255]))
color_transfer_function.add_point_from_x_color(
0.32 * discrete_color_len, np.array([225, 135, 255, 255]))
color_transfer_function.add_point_from_x_color(
0.5 * discrete_color_len, np.array([120, 120, 255, 255]))
color_transfer_function.add_point_from_x_color(
discrete_color_len - 1, np.array([0, 0, 255, 255]))
self.w = ColorTransferFunctionViewer(color_transfer_function)
self.w.show()
self.w.setGeometry(800, 500, 900, 300)
# Create Palette from ColorTransferFunction
from scipy import interpolate
xp = [point.x for point in color_transfer_function.points]
fp = [point.color_array for point in color_transfer_function.points]
interpolator = interpolate.interp1d(xp, fp, axis=0, assume_sorted=True)
result = interpolator(np.arange(discrete_color_len))
print('res', result.shape, '\n', result)
palette_array = np.array(result.round(), dtype=np.uint8)
print('rounded', palette_array)
palette = Palette(palette_array)
indexed_image = VolumeImage(norm, palette, spatial=image.spatial)
layered_image.add_layer_from_image(indexed_image, 'colored')
def color_transfer_function_to_palette(
color_transfer_function: ColorTransferFunction) -> Palette:
xp = [point.x for point in color_transfer_function.points]
fp = [point.color_array for point in color_transfer_function.points]
interpolator = interpolate.interp1d(xp, fp, axis=0, assume_sorted=True)
color_transfer_function_max_x = color_transfer_function.points[-1].x
interpolated_colors_array = interpolator(
np.arange(color_transfer_function_max_x + 1))
palette_array = np.array(interpolated_colors_array.round(), dtype=np.uint8)
return Palette(palette_array)
def create_colored_image_3(self):
active_sub_window = self.mdi.activeSubWindow()
if not isinstance(active_sub_window, LayeredImageViewerSubWindow):
return
layered_image = active_sub_window.viewer.data
layered_image.print_layers()
image = layered_image.layer_by_name('series').image
print('stat', image.array.shape, image.array.min(), image.array.max(),
image.array.dtype)
print(np.unique(image.array))
discrete_color_len = 2000
norm = (image.array / image.array.max() *
(discrete_color_len - 1)).astype(np.int)
print('norm stat', norm.shape, norm.min(), norm.max(), norm.dtype)
import colorsys
palette_array = np.zeros((discrete_color_len, 4), dtype=np.uint8)
h_min = 0
h_max = 360
s_min = 70
s_max = 100
b = 80
h_range = h_max - h_min
s_range = s_max - s_min
color_range = h_range * s_range
color_delta = color_range / discrete_color_len
for i in range(discrete_color_len):
v = color_delta * i
h = h_min + (v // s_range)
s = s_min + (v % s_range)
# h = h_max - h
print('i', i, ' hsv', h, s, b)
hsv_decimal = (h / 360, s / 100, b / 100)
rgb_decimal = colorsys.hsv_to_rgb(*hsv_decimal)
rgb = tuple(round(c * 255) for c in rgb_decimal)
# palette_array[discrete_color_len - i - 1] = [*rgb, 255]
palette_array[i] = [*rgb, 255]
print('res conv', palette_array[i])
palette = Palette(palette_array)
indexed_image = VolumeImage(norm, palette, spatial=image.spatial)
layered_image.add_layer_from_image(indexed_image, 'colored')
def create_colored_image_2(self):
active_sub_window = self.mdi.activeSubWindow()
if not isinstance(active_sub_window, LayeredImageViewerSubWindow):
return
layered_image = active_sub_window.viewer.data
layered_image.print_layers()
image = layered_image.layer_by_name('series').image
print('stat', image.array.shape, image.array.min(), image.array.max(),
image.array.dtype)
print(np.unique(image.array))
norm = (image.array / image.array.max() * 511).astype(np.int)
print('norm stat', norm.shape, norm.min(), norm.max(), norm.dtype)
import colorsys
palette_array = np.zeros((512, 4), dtype=np.uint8)
h = 0
b = 80
i = 0
while i < 512:
for s in range(60, 100):
print('i', i, ' hsv', h, s, b)
hsv_decimal = (h / 360, s / 100, b / 100)
rgb_decimal = colorsys.hsv_to_rgb(*hsv_decimal)
rgb = tuple(round(c * 255) for c in rgb_decimal)
palette_array[i] = [*rgb, 255]
print('res conv', palette_array[i])
i += 1
if i >= 512:
break
h += 24
palette = Palette(palette_array)
indexed_image = VolumeImage(norm, palette, spatial=image.spatial)
layered_image.add_layer_from_image(indexed_image, 'colored')
def overlay_sibling_dirs_images(
self, data: Data, data_viewer_sub_windows: DataViewerSubWindow):
if isinstance(data, LayeredImage):
first_layer = data.layers[0]
first_layer_image_name = first_layer.image_path.name
layers_dir = first_layer.path.parent
for new_layer_name, layer_properties in self.config_data[
'layers'].items():
new_layer_image_path = layers_dir / new_layer_name / first_layer_image_name
if new_layer_image_path.exists():
palette_property = layer_properties.get('palette')
palette = palette_property and Palette.from_sparse_index_list(
list(palette_property))
new_image = self.loading_manager.load_file(
new_layer_image_path, palette=palette)
new_image_layer = data.add_layer_from_image(
new_image, new_layer_name)
layer_opacity = layer_properties['opacity']
for data_viewer_sub_window in data_viewer_sub_windows:
layered_image_viewer = data_viewer_sub_window.viewer
layered_image_viewer.layer_view_by_model(
new_image_layer).opacity = layer_opacity