Python skimage.transform.resize

如何解决Python skimage.transform.resize

我遇到了一些我不明白的麻烦，我正在尝试调整图像大小以将占用的内存减少到 1Mo 并保持原来的高/宽比例。

这是我的代码：

import skimage
from skimage.io import imread,imsave
from skimage.transform import resize
import matplotlib.pyplot as plt
import numpy as np

#Original image
croa = imread("https://gitlab.emse.fr/gavet/mooc_ti_data/-/raw/master/croatie.jpg?inline=false")

def s2(s0):           #function to calculate the height to keep the original ratio
    i = croa.shape[0]
    j = croa.shape[1]
    ratio = j/i
    return int(ratio * s0)

def count(image):          #function to count the memory taken by the image
    if image.shape != (0,):
        res = 1
        for i in range(len(image.shape)):
            res = res * image.shape[i]
        return res
    else:
        return 0

def distance(s0):      #function to calculate how far I am from 1Mo.
    bis = resize(croa,(s0,s2(s0),3),anti_aliasing=True)
    no = count(bis)
    return no-10**6

def my_resize(image):
    s0 = croa.shape[0]
    
    begin= 200
    end= s0
    
    epsilon = 1
    my_distance = distance(begin)
    
    follow = [0]
    
    i = 0
    while abs(my_distance) > epsilon:
        
        s = (begin + end)//2
        follow.append(s)
        
        i = i+1
        
        if follow[i-1]==follow[i]:
            a = resize(croa,(s,s2(s),anti_aliasing=True)
            plt.imshow(a)
            plt.show()
            return a
        print(s)
        my_distance = distance(s)
        
        if my_distance >0:
            end = s
        else:
            begin = s
    return s

这是我得到的错误，我尝试使用和不使用 anti_aliasing。

---------------------------------------------------------------------------
Traceback (most recent call last)
<ipython-input-11-b8f1eaf3fb1e> in <module>
      1 # Test visible
      2 import numpy.testing as tests
----> 3 I2 = redimensionne_croatie()
      4 assert(isinstance(I2,np.ndarray))
      5 tests.assert_equal(I2.dtype,np.uint8)

<ipython-input-10-335574f23646> in redimensionne_croatie()
     26 
     27         if suivi[i-1]==suivi[i]:
---> 28             a = resize(croa,anti_aliasing=True)
     29             plt.imshow(a)
     30             plt.show()

/opt/conda/lib/python3.8/site-packages/skimage/transform/_warps.py in resize(image,output_shape,order,mode,cval,clip,preserve_range,anti_aliasing,anti_aliasing_sigma)
    145                              "documentation of numpy.pad for more info.")
    146 
--> 147         image = ndi.gaussian_filter(image,anti_aliasing_sigma,148                                     cval=cval,mode=ndi_mode)
    149 

/opt/conda/lib/python3.8/site-packages/scipy/ndimage/filters.py in gaussian_filter(input,sigma,output,truncate)
    339     if len(axes) > 0:
    340         for axis,mode in axes:
--> 341             gaussian_filter1d(input,axis,342                               mode,truncate)
    343             input = output

/opt/conda/lib/python3.8/site-packages/scipy/ndimage/filters.py in gaussian_filter1d(input,truncate)
    258     # Since we are calling correlate,not convolve,revert the kernel
    259     weights = _gaussian_kernel1d(sigma,lw)[::-1]
--> 260     return correlate1d(input,weights,0)
    261 
    262 

/opt/conda/lib/python3.8/site-packages/scipy/ndimage/filters.py in correlate1d(input,origin)
    131                          '(len(weights)-1) // 2')
    132     mode = _ni_support._extend_mode_to_code(mode)
--> 133     _nd_image.correlate1d(input,134                           origin)
    135     return output