def generateLocalPalettes(input_img, row_step, col_step, overlap_size, total_slides):
count = 0
localPalettesList = []
height = input_img.shape[0]
width = input_img.shape[1]
for i in range(0, height, row_step):
if i + row_step > height:
continue
else:
for j in range(0, width, col_step):
if j + col_step > width:
continue
else:
count += 1
if count <= total_slides:
row_step_final = row_step if ((i + row_step + overlap_size) > height) else (row_step + overlap_size)
col_step_final = col_step if ((j + col_step + overlap_size) > width) else (col_step + overlap_size)
sample_img = input_img[i : i + row_step_final, j : j + col_step_final, :]
hist3D = Hist3D(sample_img, num_bins=16, color_space='Lab')
color_coordinates = hist3D.colorCoordinates()
color_densities = hist3D.colorDensities()
rgb_colors = hist3D.rgbColors()
palette_selection = PaletteSelection(color_coordinates,
color_densities, rgb_colors,
num_colors=5, sigma=70.0)
localPalettesList.append(palette_selection.paletteColors())
else:
break
return localPalettesList
def generateGlobalPalettes(input_img, palette_num=5):
hist3D = Hist3D(input_img, num_bins=16, color_space='Lab')
color_coordinates = hist3D.colorCoordinates()
color_densities = hist3D.colorDensities()
rgb_colors = hist3D.rgbColors()
palette_selection = PaletteSelection(color_coordinates,
color_densities, rgb_colors,
num_colors=palette_num, sigma=70.0)
return palette_selection.paletteColors()
