时间戳

首页 > 解决方案 > 如何在灰度图像集上创建 keras conv2d 层

python - 如何在灰度图像集上创建 keras conv2d 层

问题描述

我创建了这个 NN

#Encoder
encoder_input = Input(shape=(1,height, width))
encoder_output = Conv2D(64, (3,3), activation='relu', padding='same', strides=2)(encoder_input)
encoder_output = Conv2D(128, (3,3), activation='relu', padding='same')(encoder_output)
encoder_output = Conv2D(128, (3,3), activation='relu', padding='same', strides=2)(encoder_output)
encoder_output = Conv2D(256, (3,3), activation='relu', padding='same')(encoder_output)
encoder_output = Conv2D(256, (3,3), activation='relu', padding='same', strides=2)(encoder_output)
encoder_output = Conv2D(512, (3,3), activation='relu', padding='same')(encoder_output)
encoder_output = Conv2D(512, (3,3), activation='relu', padding='same')(encoder_output)
encoder_output = Conv2D(256, (3,3), activation='relu', padding='same')(encoder_output)
#Decoder
decoder_output = Conv2D(128, (3,3), activation='relu', padding='same')(encoder_output)
decoder_output = UpSampling2D((2, 2))(decoder_output)
decoder_output = Conv2D(64, (3,3), activation='relu', padding='same')(decoder_output)
decoder_output = UpSampling2D((2, 2))(decoder_output)
decoder_output = Conv2D(32, (3,3), activation='relu', padding='same')(decoder_output)
decoder_output = Conv2D(16, (3,3), activation='relu', padding='same')(decoder_output)
decoder_output = Conv2D(2, (3, 3), activation='tanh', padding='same')(decoder_output)
decoder_output = UpSampling2D((2, 2))(decoder_output)
model = Model(inputs=encoder_input, outputs=decoder_output)
model.compile(optimizer='adam', loss='mse' , metrics=['accuracy'])
clean_images = model.fit(train_images,y_train_red, epochs=200)

和火车图像是由

train_images = np.array([ImageOperation.resizeImage(cv2.imread(train_path + str(i) + ".jpg"), height, width) for i in
                range(train_size)])

y_train_red = [img[:, :, 2]/255 for img in train_images]

train_images = np.array([ImageOperation.grayImg(item) for item in train_images])

当我执行代码时，我收到以下错误

检查输入时出错：预期 input_1 有 4 个维度，但得到了形状为 (10, 200, 200) 的数组如何解决？

标签： pythontensorflowkeras

解决方案

您的图像是 2D（高度 x 宽度），而它需要 3D 图像。重塑您的图像以添加其他尺寸，例如，

train_images = train_images.reshape(train_size, height, width, 1)

推荐阅读