Cropping3D 层
Cropping3D 类
keras.layers.Cropping3D(
cropping=((1, 1), (1, 1), (1, 1)), data_format=None, **kwargs
)
用于 3D 数据（例如空间或时空数据）的裁剪层。
示例
>>> input_shape = (2, 28, 28, 10, 3)
>>> x = np.arange(np.prod(input_shape)).reshape(input_shape)
>>> y = keras.layers.Cropping3D(cropping=(2, 4, 2))(x)
>>> y.shape
(2, 24, 20, 6, 3)
参数
- cropping: 整数，或 3 个整数的元组，或 3 个包含 2 个整数的元组的元组。
- 如果为整数：相同的对称裁剪应用于深度、高度和宽度。
- 如果为 3 个整数的元组：解释为深度、高度和宽度的三个不同的对称裁剪值：
(symmetric_dim1_crop, symmetric_dim2_crop, symmetric_dim3_crop)。 - 如果为 3 个包含 2 个整数的元组的元组：解释为
((left_dim1_crop, right_dim1_crop), (left_dim2_crop, right_dim2_crop), (left_dim3_crop, right_dim3_crop))。
- data_format: 字符串，可以是
"channels_last"（默认）或"channels_first"。输入中维度的顺序。"channels_last"对应于形状为(batch_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)的输入，而"channels_first"对应于形状为(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3)的输入。如果未指定，则使用在您的 Keras 配置文件~/.keras/keras.json（如果存在）中找到的image_data_format值。默认为"channels_last"。
输入形状
5D 张量，形状为：- 如果 data_format 为 "channels_last"：(batch_size, first_axis_to_crop, second_axis_to_crop, third_axis_to_crop, channels) - 如果 data_format 为 "channels_first"：(batch_size, channels, first_axis_to_crop, second_axis_to_crop, third_axis_to_crop)
输出形状
5D 张量，形状为：- 如果 data_format 为 "channels_last"：(batch_size, first_cropped_axis, second_cropped_axis, third_cropped_axis, channels) - 如果 data_format 为 "channels_first"：(batch_size, channels, first_cropped_axis, second_cropped_axis, third_cropped_axis)