如何使用 Numpy 和 Matplotlib（opencv 或 scikit 图像，以防不可能）在 RGB 图像之上叠加灰度蒙版

Question

我有 2 张来自 Carvana Image Dataset 的图像，其中图像为 jpg，遮罩为 gif。我已将蒙版转换为 0 或 1 的灰度，现在想将其覆盖在图像上以查看这 3 个原始蒙版，使用 matplotlib 并排叠加。正确的做法是什么？

from PIL import Image

def get_pair(image_path, mask_path):
    image = np.array(Image.open(image_path).convert('RGB'))
    mask = np.array(Image.open(mask_path).convert('L'), dtype = np.float32) # Mask should be Grayscale so each value is either 0 or 255
    mask[mask == 255.0] = 1.0 # whereever there is 255, convert it to 1: (1 == 255 == White)
    return image, mask

一种方法可以是：


image, mask = data[0]
image = image / 255
mask = np.stack((mask,)*3, axis=-1)

blended = image * mask
plt.imshow(blended)

但它只显示汽车和其他所有东西都是黑色的

下面是2张图片

我想将这 3 个绘制为：

Answer 1

您的期望可能有误。

... but it shows only the car and everything else as black

二进制掩码通常是这样操作的。

以下自包含代码（相应地保存了上面的图像）可能会解释发生了什么。注意 blended1 = ...

附近的评论


from PIL import Image
import numpy as np
from matplotlib import pyplot as plt

def get_pair(image_path, mask_path):
    image = np.array(Image.open(image_path).convert('RGB'))
    mask = np.array(Image.open(mask_path).convert('L'), dtype = np.float32) # Mask should be Grayscale so each value is either 0 or 255
    mask[mask == 255.0] = 1.0 # whereever there is 255, convert it to 1: (1 == 255 == White)
    return image, mask 

img, mask = get_pair("img.jpg", "mask.gif")
print(f"{img.shape=}")  #      -> img.shape=(1280, 1918, 3)
print(f"{mask.shape=}")  #     -> img.shape=(1280, 1918)

mask2 = np.stack((mask,)*3, axis=-1)
print(f"{mask2.shape=}")  # -> img.shape=(1280, 1918, 3)

# rescale image
img = img /255

# set every pixel to (0, 0, 0) (black) where mask is 0 and
# keep every pixel unchanged where mask is 1
# this is how a mask is usually applied
blended1 = img*mask2

# set every pixel to (1, 1, 1) (white) where mask is 1 and
# keep every pixel unchanged where mask is 0


blended2 = np.clip(img+mask2, 0, 1)

fig, axx = plt.subplots(1, 4, figsize=(8, 18))

for ax, arr, title in zip(axx,
                        [img, mask, blended1, blended2],
                        ["original", "mask", "blended1", "blended2"]):
    ax.imshow(arr)
    ax.axis("off")
    ax.set_title(title)

plt.show()

生成的图像：

如何使用 Numpy 和 Matplotlib（opencv 或 scikit 图像，以防不可能）在 RGB 图像之上叠加灰度蒙版

How to overlay Grayscale Mask on top of RGB image using Numpy and Matplotlib ( opencv or scikit image in case not possible)

python

numpy

matplotlib

python-imaging-library