python 灰度图像转彩色_是否有任何好的色彩映射表，可以使用python的PIL将灰度图像转换为彩色图像？...

Matplotlib has a lot of good color maps, but is bad in performance. I'm writing some code to make gray-scale image colorful where interpolate with color map is a good idea. I wonder whether there are open source color maps available or demo code to use Pillow to convert gray-scale images into colorful ones via colormap?

Clarify:

Matplotlib is good for demo use, but bad performace for thounsands of images.

You can map grayscale images to colormaps to get colorful ones.

Demo:

The first image is grayscale, second is mapped in 'jet' cmap, third being 'hot'.

The problem is that I do not know much about colors, and I'd like to achieve such effects in PIL for better performance.

解决方案

I figured out with the duplicate answer mentioned by @ImportanceOfBeingErnest (How to convert Numpy array to PIL image applying matplotlib colormap)

import matplotlib as mpl

import matplotlib.pyplot as plt

import matplotlib.image as mpimg

import numpy as np

import timeit

from PIL import Image

def pil_test():

cm_hot = mpl.cm.get_cmap('hot')

img_src = Image.open('test.jpg').convert('L')

img_src.thumbnail((512,512))

im = np.array(img_src)

im = cm_hot(im)

im = np.uint8(im * 255)

im = Image.fromarray(im)

im.save('test_hot.jpg')

def rgb2gray(rgb):

return np.dot(rgb[:,:,:3], [0.299, 0.587, 0.114])

def plt_test():

img_src = mpimg.imread('test.jpg')

im = rgb2gray(img_src)

f = plt.figure(figsize=(4, 4), dpi=128)

plt.axis('off')

plt.imshow(im, cmap='hot')

plt.savefig('test2_hot.jpg', dpi=f.dpi)

plt.close()

t = timeit.timeit(pil_test, number=30)

print('PIL: %s' % t)

t = timeit.timeit(plt_test, number=30)

print('PLT: %s' % t)

The performance result is:

PIL: 1.7473899199976586

PLT: 10.632971412000188

They both give me similar result with hot color map.