"""
Python implementation of the color map function for the PASCAL VOC data set.
Official Matlab version can be found in the PASCAL VOC devkit
http://host.robots.ox.ac.uk/pascal/VOC/voc2012/index.html#devkit
"""
import numpy as np
from skimage.io import imshow
import matplotlib.pyplot as plt
def color_map(N=256, normalized=False):
def bitget(byteval, idx):
return ((byteval & (1 << idx)) != 0)
dtype = 'float32' if normalized else 'uint8'
cmap = np.zeros((N, 3), dtype=dtype)
for i in range(N):
r = g = b = 0
c = i
for j in range(8):
r = r | (bitget(c, 0) << 7-j)
g = g | (bitget(c, 1) << 7-j)
b = b | (bitget(c, 2) << 7-j)
c = c >> 3
cmap[i] = np.array([r, g, b])
cmap = cmap/255 if normalized else cmap
return cmap
def color_map_viz():
labels = ['background', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor', 'void']
nclasses = 21
row_size = 50
col_size = 500
cmap = color_map()
array = np.empty((row_size*(nclasses+1), col_size, cmap.shape[1]), dtype=cmap.dtype)
for i in range(nclasses):
array[i*row_size:i*row_size+row_size, :] = cmap[i]
array[nclasses*row_size:nclasses*row_size+row_size, :] = cmap[-1]
imshow(array)
plt.yticks([row_size*i+row_size/2 for i in range(nclasses+1)], labels)
plt.xticks([])
plt.show()