Layer

Similar to the C++ bindings this is the base class for all layer types, unlike C++ there is no reason to actually use this type as casting down the inheritance chain is done implicitly. We can however use this to indicate a return type for type hinting.

def some_function() -> psapi.Layer_8bit:
        '''
        Return a layer type
        '''
        pass

This is why we dont actually specify any constructors for the Layer class. If you try and construct a layer object you will get an error

layer = psapi.Layer_8bit() # -> TypeError: psapi.Layer_8bit: No constructor defined!

Similarly the Layer<>::Params class from C++ is not implemented here but rather the arguments are implemented as kwargs for the individual constructors

Class Reference Layer

class psapi.Layer_8bit

Base type that all layers inherit from, this class should not be instantiated and instead the derivatives such as psapi.GroupLayer_8bit or psapi.ImageLayer_8bit should be used (with the appropriate bit depth).

Attributes:

namestr

The name of the layer, cannot be longer than 255

layer_masknp.ndarray

The pixel mask applied to the layer, read only

blend_modeenum.BlendMode

The blend mode of the layer, ‘Passthrough’ is reserved for group layers

opacityint

The layers opacity from 0-255 with 255 being 100%

widthint

The width of the layer ranging up to 30,000 for PSD and 300,000 for PSB, this does not have to match the files width

heightint

The height of the layer ranging up to 30,000 for PSD and 300,000 for PSB, this does not have to match the files height

center_xfloat

The center of the layer in regards to the canvas, a layer at center_x = 0 is perfectly centered around the document

center_yfloat

The center of the layer in regards to the canvas, a layer at center_y = 0 is perfectly centered around the document

get_mask_data(self: psapi.Layer_8bit, do_copy: bool = True) → numpy.ndarray[numpy.uint8]

Get the pixel mask data associated with the layer (if it exists), if it doesnt a warning gets raised and a null-size numpy.ndarray is returned.

The size of the mask is not necessarily the same as the layer

Parameters:

do_copy (bool) – Whether or not to copy the image data on extraction, if False the mask channel is freed

Returns:

The extracted channel with dimensions (mask_height, mask_width)

Return type:

numpy.ndarray