如何修复TypeError: unhashable type: 'numpy.ndarray'错误？

错误原因 #

np.argmax(predict_x, axis=1)返回的是一维numpy数组（哪怕只有一个预测结果，格式也是类似array([3])的数组），而字典dic的键是整数类型。numpy数组属于不可哈希类型，无法直接作为字典的键，因此触发该错误。

修复方案 #

从classes_x这个一维数组中提取出单个整数元素即可，三种常用方式任选其一：

• 通过索引取值：classes_x[0]
• 转换为Python原生整数：int(classes_x)
• 使用numpy数组的.item()方法：classes_x.item()

修改后的完整代码 #

import numpy as np
import cv2

def fix_dimension(img):
    new_img = np.zeros((28, 28, 3))
    for i in range(3):
        new_img[:, :, i] = img
    return new_img


def show_results():
    dic = {}
    characters = '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ'
    for i, c in enumerate(characters):
        dic[i] = c

    output = []
    for i, ch in enumerate(char):  # iterating over the characters
        img_ = cv2.resize(ch, (28, 28), interpolation=cv2.INTER_AREA)
        img = fix_dimension(img_)
        img = img.reshape(1, 28, 28, 3)  # preparing image for the model
        # predicted = model.predict_classes(img, verbose=0) #predicting the class
        predict_x = model.predict(img)
        classes_x = np.argmax(predict_x, axis=1)
        # 修复此处，提取数组中的整数元素
        character = dic[classes_x[0]]
        output.append(character)  # storing the result in a list

    plate_number = ''.join(output)
    return plate_number


print(show_results())

内容的提问来源于stack exchange，提问作者Akshaya K Ravikumar