绘制形状为 (200, 200) 的 Numpy 数组显示垂直线而不是正方形

Question

刚开始学习Python3.7.7.

我正在尝试使用绘图将 NIFTI 图像显示为具有 float32 元素的 numpy 数组。

这是显示图像的代码：

import os
import SimpleITK as sitk
import numpy as np
import matplotlib.pyplot as plt
import cv2

def plot_grey_images_as_figure(img1, img2, title1, title2):
    """
    Show img1 and img2 as a single figure using matplotlib.pylot.

    Show img1 and img2 as a single figure using matplotlib.pylot with the titles
    title1 for img1 and title2 for img2.

    Parameters:
    img1 (array-like or PIL image): Image to show first.
    img2 (array-like or PIL image): Image to show second.
    title1 (string) : Title for image 1.
    title2 (string) : Title for image 2.

    Returns:
    Nothing.

    """    

    plt.subplot(121), plt.imshow(img1, cmap = 'gray')
    plt.title(title1), plt.xticks([]), plt.yticks([])

    plt.subplot(122), plt.imshow(img2, cmap = 'gray')
    plt.title(title2), plt.xticks([]), plt.yticks([])

    plt.show()

    return

这是我在显示图像之前预处理图像的方式：

def preprocessing_array(array, rows_standard, cols_standard, debug): # array shape is (48, 240, 240)

    image_rows_Dataset = np.shape(array)[1]   
    image_cols_Dataset = np.shape(array)[2]

    num_rows_1 = ((image_rows_Dataset // 2) - (rows_standard // 2)) #  20
    num_rows_2 = ((image_rows_Dataset // 2) + (rows_standard // 2)) # 220
    num_cols_1 = ((image_cols_Dataset // 2) - (cols_standard // 2)) #  20
    num_cols_2 = ((image_cols_Dataset // 2) + (cols_standard // 2)) # 220

    array = array[:, num_rows_1:num_rows_2, num_cols_1:num_cols_2]


    ### ------ New Axis --------------------------------------------------------
    # Add a new axis to denote that this is a one channel image.
    array  = array[..., np.newaxis] 

    return array  # array shape is (48, 200, 200, 1)

要显示图像，我这样做：

# D is a dataset with shape (960, 2, 200, 200, 1) with float32 elements.
print("Shape: ", D[:,0,:][0].shape)
nifti.plot_grey_images_as_figure(D[:,0,:][0][:,-1], D[:,1,:][0][:,-1], "mask", "output")

我得到这个输出：

为什么我得到的是线条而不是方块？

也许问题是我添加了一个新轴，然后我删除了它，因为不允许我绘制形状为 (200, 200, 1).

的图像

Answer 1

图片切片不正确。你的情节功能应该是

base = D[:,0,:]
img1 = base[0][:, :, 0] # Shape of (200, 200)
img2 = base[1][:, :, 0]
nifti.plot_grey_images_as_figure(img1, img2, "mask", "output")

Answer 2

使用numpy.sqeeze() 删除大小一维。问题在于将图像作为非二维数组传递。挤压帮助我们沿着 axis=2 降低尺寸，使形状从 (200, 200, 1) 到 (200, 200)。

import numpy as np
np.queeze(D[:,0,:][0], axis=2).shape
# (200, 200)

建议的改进

# Choose the index i (axis=0)
i = 0 # Values (0, 1, ..., 960)

# Extract mask and output images
img1 = D[i,0,:,:,0] # shape (200, 200) --> mask
img2 = D[i,1,:,:,0] # shape (200, 200) --> output
nifti.plot_grey_images_as_figure(img1, img2, "mask", "output")

参考

numpy.squeeze() documentation

绘制形状为 (200, 200) 的 Numpy 数组显示垂直线而不是正方形

Plot a Numpy array with shape (200, 200) shows a vertical line instead of a square

python

numpy

matplotlib

plot

itk

建议的改进

参考