[英]How to efficiently convert image labels to RGB values?
I have a dictionary that maps classes to RGB values:我有一个将类映射到 RGB 值的字典:
label_to_color = {
0: [128, 64, 128],
1: [244, 35, 232],
2: [ 70, 70, 70],
3: [102, 102, 156],
4: [190, 153, 153],
5: [153, 153, 153]
}
I'm replacing the classes in the image with RGB values like below:我正在用 RGB 值替换图像中的类,如下所示:
def mask2pixel(image):
h,w = image.shape
im = np.zeros((h,w,3))
for i in range(h):
for j in range(w):
im[i,j,:] = label_to_color[image[i,j]]
return im.astype(int)
image = cv2.imread(im_path,-1)
print(image.shape) # 1200x720
print(image[0,0]) # 0
colormap = mask2pixel(image)
print(colormap.shape) # 1200x720x3
print(colormap[0,0]) # array([128, 64,128])
Is there any more efficient way of doing this?有没有更有效的方法来做到这一点?
Don't iterate the pixels!不要迭代像素! Iterate the colors, and use NumPy's boolean index arrays .
迭代颜色,并使用 NumPy 的布尔索引数组。
That'd be a pure NumPy solution:那将是一个纯粹的 NumPy 解决方案:
import numpy as np
label_to_color = {
0: [128, 64, 128],
1: [244, 35, 232],
2: [ 70, 70, 70],
3: [102, 102, 156],
4: [190, 153, 153],
5: [153, 153, 153]
}
img_classes = np.random.randint(0, 6, (20, 30), dtype=np.uint8)
h, w = img_classes.shape
img_rgb = np.zeros((h, w, 3), dtype=np.uint8)
for gray, rgb in label_to_color.items():
img_rgb[img_classes == gray, :] = rgb
import matplotlib.pyplot as plt
plt.figure(figsize=(16, 8))
plt.subplot(1, 2, 1), plt.imshow(img_classes)
plt.subplot(1, 2, 2), plt.imshow(img_rgb)
plt.tight_layout(), plt.show()
The corresponding output:相应的输出:
Since you have python-imaging-library in your tags, there'd be also the option to use Pillow's image mode P
to create an indexed image, and provide the colors as a palette :由于您的标签中有python-imaging-library ,因此还可以选择使用 Pillow 的图像模式
P
创建索引图像,并提供颜色作为调色板:
import numpy as np
from PIL import Image
label_to_color = {
0: [128, 64, 128],
1: [244, 35, 232],
2: [ 70, 70, 70],
3: [102, 102, 156],
4: [190, 153, 153],
5: [153, 153, 153]
}
img_classes = np.random.randint(0, 6, (20, 30), dtype=np.uint8)
img_classes = Image.fromarray(img_classes, 'L')
img_classes_p = img_classes.convert('P')
img_classes_p.putpalette(
[rgb for pixel in label_to_color.values() for rgb in pixel])
img_rgb = img_classes_p.convert('RGB')
import matplotlib.pyplot as plt
plt.figure(figsize=(24, 8))
plt.subplot(1, 3, 1), plt.imshow(img_classes)
plt.subplot(1, 3, 2), plt.imshow(img_classes_p)
plt.subplot(1, 3, 3), plt.imshow(img_rgb)
plt.tight_layout(), plt.show()
The output:输出:
----------------------------------------
System information
----------------------------------------
Platform: Windows-10-10.0.19041-SP0
Python: 3.9.1
PyCharm: 2021.1.2
Matplotlib: 3.4.2
NumPy: 1.20.3
Pillow: 8.2.0
----------------------------------------
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