deep-learning - Keras:单个图像的model.predict

Question

我想对Keras的单个图像做出预测。我已经训练了模型，所以我只是在加载重量。

from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense
from keras import backend as K
import numpy as np
import cv2

# dimensions of our images.
img_width, img_height = 150, 150



def create_model():
  if K.image_data_format() == 'channels_first':
    input_shape = (3, img_width, img_height)
  else:
    input_shape = (img_width, img_height, 3)

  model = Sequential()
  model.add(Conv2D(32, (3, 3), input_shape=input_shape))
  model.add(Activation('relu'))
  model.add(MaxPooling2D(pool_size=(2, 2)))

  model.add(Conv2D(32, (3, 3)))
  model.add(Activation('relu'))
  model.add(MaxPooling2D(pool_size=(2, 2)))

  model.add(Conv2D(64, (3, 3)))
  model.add(Activation('relu'))
  model.add(MaxPooling2D(pool_size=(2, 2)))

  model.add(Flatten())
  model.add(Dense(64))
  model.add(Activation('relu'))
  model.add(Dropout(0.5))
  model.add(Dense(1))
  model.add(Activation('sigmoid'))

  return model


img = cv2.imread('./test1/1.jpg')
model = create_model()
model.load_weights('./weight.h5')
model.predict(img)

我正在使用以下方式加载图像：

img = cv2.imread('./test1/1.jpg')

并使用模型的预测功能：

 model.predict(img)

但是我得到了错误：

ValueError: Error when checking : expected conv2d_1_input to have 4 dimensions, but got array with shape (499, 381, 3)

我应该如何对单个图像进行预测？

Answer 1

由于您是在迷你批次上训练模型的，因此您输入的是形状为[batch_size, image_width, image_height, number_of_channels]的张量。

进行预测时，即使只有一张图像，也必须尊重这种形状。您输入的内容应为：[1, image_width, image_height, number_of_channels]。

您可以轻松地在numpy中执行此操作。假设您有一张5x5x3的图片：

    >>> x = np.random.randint(0,10,(5,5,3))
    >>> x.shape
    >>> (5, 5, 3)
    >>> x = np.expand_dims(x, axis=0)
    >>> x.shape
    >>> (1, 5, 5, 3)

现在x是4级张量！