Python NumPy - 将数组坐标视为序列

Question

我正在输入一个 numpy 数组，该数组是从图像生成到函数中的。该函数通过水平重复图像并移动某些像素来制作自动立体图。

这是通过另一个 numpy 数组完成的，自动立体图数组的坐标 [r, c] 基于纹理数组的坐标，其中一些数学修改了坐标。

问题是，代码将其中一个坐标视为序列。该代码在索引方面存在一些问题。

import numpy as np
import matplotlib.pyplot as plt
import skimage, skimage.io
from PIL import Image
#%matplotlib inline

plt.rcParams['figure.dpi'] = 150


def normalize(depthmap):
    "Normalizes values of depthmap to [0, 1] range."
    if depthmap.max() > depthmap.min():
        return (depthmap - depthmap.min()) / (depthmap.max() - depthmap.min())
    else:
        return depthmap
    
def display(img, colorbar=False):
    "Displays an image."
    
    plt.figure(figsize=(10, 10))
    if len(img.shape) == 2:
        i = skimage.io.imshow(img, cmap='gray')
        #pass
    else:
        #pass
        i = skimage.io.imshow(img)
    i = skimage.io.imshow(img)
    if colorbar:
        plt.colorbar(i, shrink=0.5, label='depth')
    plt.tight_layout()
    print("display called")



def make_pattern(shape=(16, 16), levels=64):
    "Creates a pattern from gray values."
    return np.random.randint(0, levels - 1, shape) / levels


def create_circular_depthmap(shape=(600, 800), center=None, radius=100):
    "Creates a circular depthmap, centered on the image."
    depthmap = np.zeros(shape, dtype=float)
    r = np.arange(depthmap.shape[0])
    c = np.arange(depthmap.shape[1])
    R, C = np.meshgrid(r, c, indexing='ij')
    if center is None:
        center = np.array([r.max() / 2, c.max() / 2])
    d = np.sqrt((R - center[0])**2 + (C - center[1])**2)
    depthmap += (d < radius)
    return depthmap  


def make_autostereogram(depthmap, pattern, shift_amplitude=0.1, invert=False):
    "Creates an autostereogram from depthmap and pattern."
    print("make_autostereogram called")
    depthmap = normalize(depthmap)
    if invert:
        depthmap = 1 - depthmap
    autostereogram = np.zeros_like(depthmap, dtype=pattern.dtype)
    for r in np.arange(autostereogram.shape[0]):
        for c in np.arange(autostereogram.shape[1]):
            if c < pattern.shape[1]:
                autostereogram[r, c] = pattern[int(r % pattern.shape[0]), c] #pattern[r, c] #
            else:
                shift = int(depthmap[r, c] * shift_amplitude * pattern.shape[1])
                autostereogram[r, c] = autostereogram[r, int(c - pattern.shape[1] + shift)] #autostereogram[r, c]#

    return autostereogram


img = blank_image()


texture= Image.open('marble.png')
texture.show()
    


depthmap = create_circular_depthmap(radius=150)

#print("depthmap: ", depthmap)

depthmapImg = Image.fromarray(normalize(depthmap))



newPattern = np.array(texture)

print("new pattern: ", type(newPattern))



autostereogram2 = make_autostereogram(depthmap, newPattern)
"""
display(autostereogram)

autostereogram2.show()"""

错误信息：

TypeError: only length-1 arrays can be converted to Python scalars

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\geniu\OneDrive\GW\Spring_2024\CSCI_6527\final_project.py", line 171, in <module>
    autostereogram2 = make_autostereogram(depthmap, newPattern)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\geniu\OneDrive\GW\Spring_2024\CSCI_6527\final_project.py", line 85, in make_autostereogram
    autostereogram[r, c] = pattern[int(r % pattern.shape[0]), c] #pattern[r, c] #
    ~~~~~~~~~~~~~~^^^^^^
ValueError: setting an array element with a sequence.

Answer 1

罪魁祸首：

texture= Image.open('marble.png')

我假设您的图像是彩色的（或者您将其作为多通道图像加载），这意味着它有 3 个通道，因此您的图案由 3 个通道组成。

因此，当您访问

pattern[int(r % pattern.shape[0]), c]

时，这意味着您仅为三个通道中的两个指定两个索引。第三个通道是一个序列，因为您没有为其指定索引。

因此，如果您想继续使用此逻辑，您需要将图像转换为灰度或指定第三个索引以按原样使用图像。