CenterCrop class
keras.layers.CenterCrop(height, width, data_format=None, **kwargs)
A preprocessing layer which crops images.
This layers crops the central portion of the images to a target size. If an image is smaller than the target size, it will be resized and cropped so as to return the largest possible window in the image that matches the target aspect ratio.
Input pixel values can be of any range (e.g. [0., 1.) or [0, 255]).
Input shape
3D (unbatched) or 4D (batched) tensor with shape: (..., height, width, channels), in "channels_last" format, or (..., channels, height, width), in "channels_first" format.
Output shape
3D (unbatched) or 4D (batched) tensor with shape: (..., target_height, target_width, channels), or (..., channels, target_height, target_width), in "channels_first" format.
If the input height/width is even and the target height/width is odd (or inversely), the input image is left-padded by 1 pixel.
Note: This layer is safe to use inside a tf.data pipeline (independently of which backend you're using).
Arguments
"channels_last" or "channels_first". The ordering of the dimensions in the inputs. "channels_last" corresponds to inputs with shape (batch, height, width, channels) while "channels_first" corresponds to inputs with shape (batch, channels, height, width). It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. If you never set it, then it will be "channels_last".RetroSearch is an open source project built by @garambo | Open a GitHub Issue
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