ValueError: Error when checking input: expected dense_1_input to have shape (9,) but got array with shape (1,)

Question

嗨，所以我构建了一个 DNN 网络来使用对象的特征对图像中的某些对象进行分类，如下所示：

contours, _ = cv2.findContours(imgthresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)

for contour in contours:
    features = np.array([])
    (x_start, y_start, character_width, character_height) = cv2.boundingRect(contour)
    x_end = x_start + character_width
    y_end = y_start + character_height
    character_area = character_width * character_height
    features = np.append(features, [character_width, character_height, character_area, x_start,
                                    y_start, x_end, y_end, image_width, image_height])

    print(features)
    print(features.shape)
    cv2.rectangle(image, (x_start, y_start), (x_end, y_end), (0, 255, 0), thickness=1)

print(features) 输出为：

[  5.   1.   5. 105.  99. 110. 100. 100. 117.]

和print(features.shape)是：

(9,)

我使用以下代码构建并训练了一个 DNN：

model = Sequential()

model.add(Dense(50, input_dim=9, activation='relu'))

model.add(Dropout(0.5))

model.add(Dense(40, activation='relu'))

model.add(Dropout(0.5))

model.add(Dense(30,activation='relu'))

model.add(Dense(2, activation='softmax'))

输入层有9个输入特征。所以我尝试使用以下方法获得模型的预测：

model.predict_classes(features)

训练数据，一个 CSV 文件，包含 10 列（9 个特征和 1 个用于输出）

我收到以下错误：

ValueError: Error when checking input: expected dense_1_input to have shape (9,) but got array with shape (1,)

我尝试使用以下方法重塑特征数组：

np.reshape(features,(1,9)

但这也没有用。我在这个领域还是新手

Answer 1

这是一个最小的工作示例。

import numpy as np
import tensorflow as tf

def main():
    features = np.array([5, 1, 5, 105, 99, 110, 100, 100, 117])
    model = tf.keras.Sequential()
    model.add(tf.keras.layers.Dense(50, input_dim=9, activation="relu"))

    print(tf.expand_dims(features, 0))
    print(np.reshape(features, (1, 9)))

    print(model.predict_classes(np.reshape(features, (1, 9))))


if __name__ == '__main__':
    main()

如您所见，np.reshape 调用使其有效。它大致相当于 tf.expand_dims.

您当前的错误是因为您的模型需要一个批次维度。因此，如果您向它传递一个形状为 (9,) 的数组，它会推断这是一批标量，而不是大小为 9.

的单个数组

ValueError: Error when checking input: expected dense_1_input to have shape (9,) but got array with shape (1,)

ValueError: Error when checking input: expected dense_1_input to have shape (9,) but got array with shape (1,)

python

machine-learning

deep-learning

keras

valueerror