Python 获取错误：无法将大小为 122304 的数组重塑为形状 (52,28,28)
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Getting error: Cannot reshape array of size 122304 into shape (52,28,28)
提问by akrama81
I'm trying to reshape a numpy array as:
我正在尝试将一个 numpy 数组重塑为：
data3 = data3.reshape((data3.shape[0], 28, 28))
where data3is:
在哪里data3：
[[54 68 66 ..., 83 72 58]
[63 63 63 ..., 51 51 51]
[41 45 80 ..., 44 46 81]
...,
[58 60 61 ..., 75 75 81]
[56 58 59 ..., 72 75 80]
[ 4 4 4 ..., 8 8 8]]
data3.shapeis (52, 2352 )
data3.shape是 (52, 2352 )
But I keep getting the following error:
但我不断收到以下错误：
ValueError: cannot reshape array of size 122304 into shape (52,28,28)
Exception TypeError: TypeError("'NoneType' object is not callable",) in <function _remove at 0x10b6477d0> ignored
What is happening and how to fix this error?
发生了什么以及如何解决此错误？
UPDATE:
更新：
I'm doing this to obtain data3that is being used above:
我这样做data3是为了获得上面使用的：
def image_to_feature_vector(image, size=(28, 28)):
return cv2.resize(image, size).flatten()
data3 = np.array([image_to_feature_vector(cv2.imread(imagePath)) for imagePath in imagePaths])
imagePaths contains paths to all the images in my dataset. I actually want to convert the data3 to a flat list of 784-dim vectors, however the
imagePaths 包含数据集中所有图像的路径。我实际上想将 data3 转换为 a flat list of 784-dim vectors，但是
image_to_feature_vector
function converts it to a 3072-dim vector!!
函数将其转换为 3072-dim 向量！！
回答by Kaushik Nayak
You can reshape the numpy matrix arrays such that before(a x b x c..n) = after(a x b x c..n). i.e the total elements in the matrix should be same as before, In your case, you can transform it such that transformed data3 has shape (156, 28, 28) or simply :-
您可以重塑 numpy 矩阵数组，使 before(axbx c..n) = after(axbx c..n)。即矩阵中的总元素应与以前相同，在您的情况下，您可以转换它，使转换后的 data3 具有形状 (156, 28, 28) 或简单地：-
import numpy as np
data3 = np.arange(122304).reshape(52, 2352 )
data3 = data3.reshape((data3.shape[0]*3, 28, 28))
print(data3.shape)
Output is of the form
输出的形式
[[[ 0 1 2 ..., 25 26 27]
[ 28 29 30 ..., 53 54 55]
[ 56 57 58 ..., 81 82 83]
...,
[ 700 701 702 ..., 725 726 727]
[ 728 729 730 ..., 753 754 755]
[ 756 757 758 ..., 781 782 783]]
...,
[122248 122249 122250 ..., 122273 122274 122275]
[122276 122277 122278 ..., 122301 122302 122303]]]
回答by akilat90
First, your input image's number of elements should match the number of elements in the desired feature vector.
首先，输入图像的元素数量应与所需特征向量中的元素数量相匹配。
Assuming the above is satisfied, the below should work:
假设满足上述条件，以下应该可以工作：
# Reading all the images to a one numpy array. Paths of the images are in the imagePaths
data = np.array([np.array(cv2.imread(imagePaths[i])) for i in range(len(imagePaths))])
# This will contain the an array of feature vectors of the images
features = data.flatten().reshape(1, 784)
