Question

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

def threshold(imageArray):
    balanceAr = []
    newAr = imageArray
    for eachRow in imageArray:
        for eachPix in eachRow:
            avgNum = reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3])
            balanceAr.append(avgNum)
    balance = reduce(lambda x, y: x + y, balanceAr) / len(balanceAr)
    for eachRow in newAr:
        for eachPix in eachRow:
            if reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3]) > balance:
                eachPix[0] = 255
                eachPix[1] = 255
                eachPix[2] = 255
                eachPix[3] = 255
            else:
                eachPix[0] = 0
                eachPix[1] = 0
                eachPix[2] = 0
                eachPix[3] = 255
    return newAr




i = Image.open('images/numbers/0.1.png')
iar = np.asarray(i)
3iar = threshold(iar)

i2 = Image.open('images/numbers/y0.4.png')
iar2 = np.asarray(i2)
#iar2 = threshold(iar2)

i3 = Image.open('images/numbers/y0.5.png')
iar3 = np.asarray(i3)
#iar3 = threshold(iar3)

i4 = Image.open('images/sentdex.png') 
iar4 = np.asarray(i4)
#iar4 = threshold(iar4)

threshold(iar3)
fig = plt.figure()
ax1 = plt.subplot2grid((8,6), (0,0), rowspan = 4, colspan = 3)
ax2 = plt.subplot2grid((8,6), (4,0), rowspan = 4, colspan = 3)
ax3 = plt.subplot2grid((8,6), (0,3), rowspan = 4, colspan = 3)
ax4 = plt.subplot2grid((8,6), (4,3), rowspan = 4, colspan = 3)

ax1.imshow(iar)
ax2.imshow(iar2)
ax3.imshow(iar3)
ax4.imshow(iar4)

plt.show()

我得到的错误：

Warning (from warnings module):
  File "C:\WinPython-32bit-2.7.9.5\python-2.7.9\Lib\idlelib\MuditPracticals\Image_Recognition\imagerec.py", line 11
    avgNum = reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3])
RuntimeWarning: overflow encountered in ubyte_scalars

Warning (from warnings module):
  File "C:\WinPython-32bit-2.7.9.5\python-2.7.9\Lib\idlelib\MuditPracticals\Image_Recognition\imagerec.py", line 16
    if reduce(lambda x, y: x + y, eachPix[:3]) / len(eachPix[:3]) > balance:
RuntimeWarning: overflow encountered in ubyte_scalars

Traceback (most recent call last):
  File "C:\WinPython-32bit-2.7.9.5\python-2.7.9\Lib\idlelib\MuditPracticals\Image_Recognition\imagerec.py", line 47, in <module>
    threshold(iar3)
  File "C:\WinPython-32bit-2.7.9.5\python-2.7.9\Lib\idlelib\MuditPracticals\Image_Recognition\imagerec.py", line 17, in threshold
    eachPix[0] = 255
ValueError: assignment destination is read-only

Answer 1

关于溢出运行时警告：

你不应该担心这些，他们基本上告诉你的是uint_8（无符号整数）type defined by numpy的范围，通常用于图像文件，已经超出了可接受的范围。

根据提供的链接，uint_8类型的范围为：

无符号整数（0到255）

numpy只是向通知您发出溢出警告。值得庆幸的是，它会自动将结果调整为可接受范围的值。

例如：

from PIL import Image
import numpy as np

img = Image.open("/path/to/image.png")
img_array = np.asarray(img) # array values are of type uint_8 (!)

print img_array[0][0] # prints [ 12,  21,  56, 255] 

uint8_1 = img_array[0][0][3] # = 255
uint8_2 = img_array[0][0][2] # = 56

uint8_3 = uint8_1 + uint8_2 

# When executed raises a RuntimeWarning of overflow ubyte_scalars
# But! The result 'rolls over' to the acceptable range. So,
print uint8_3  # prints 55

关于实际错误：

为您的ValueError: assignment destination is read-only数组numpy分配值时，实际上会引发错误 newAr 。它提供了丰富的信息，它告诉你的是数组是read only;内容只读：您可以访问，但 无法修改 。

这样的行动：

# using img_array from previous snippet.
img_array[0][0][0] = 200

将举起ValueError。

值得庆幸的是，通过为数组设置标志参数可以轻松绕过它：

# using img_array from the previous snippet
# make it writeable 
img_array.setflags(write=True)

# Values of img_array[0][0] are, as before: [ 12,  21,  56, 255]
# changing the values for your array is possible now!
img_array[0][0][0] = 200

print img_array[0][0] # prints [ 200,  21,  56, 255]

抑制溢出运行时警告：

最后的注释：您可以随时suppress/ignore these warnings，即使这通常不是最好的主意。（控制台中的一些警告令人讨厌，但它们可以让您更清楚地了解事物）

为此，只需在导入numpy后添加以下内容：

import numpy as np
np.seterr(over='ignore')

Answer 2

I1 = Image.open（＆＃39;图像/数字/ 0.1.png＆＃39;） IAR1 = np.array（I1）

而不是asarray方法使用数组

Answer 3

尝试将y：x + y替换为y：int（x）+ int（y）

ubyte_scalars中遇到运行时警告溢出

3 个答案:

关于溢出运行时警告：

关于实际错误：

抑制溢出运行时警告：