forked from bartvdbraak/blender
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
# This sample shows the an efficient way of doing image processing
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# over Blender's images using Python.
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import bpy
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import numpy as np
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input_image_name = "Image"
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output_image_name = "NewImage"
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# Retrieve input image.
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input_image = bpy.data.images[input_image_name]
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w, h = input_image.size
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# Allocate a numpy array to manipulate pixel data.
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pixel_data = np.zeros((w, h, 4), 'f')
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# Fast copy of pixel data from bpy.data to numpy array.
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input_image.pixels.foreach_get(pixel_data.ravel())
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# Do whatever image processing you want using numpy here:
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# Example 1: Inverse red green and blue channels.
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pixel_data[:, :, :3] = 1.0 - pixel_data[:, :, :3]
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# Example 2: Change gamma on the red channel.
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pixel_data[:, :, 0] = np.power(pixel_data[:, :, 0], 1.5)
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# Create output image.
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if output_image_name in bpy.data.images:
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output_image = bpy.data.images[output_image_name]
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else:
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output_image = bpy.data.images.new(output_image_name, width=w, height=h)
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# Copy of pixel data from numpy array back to the output image.
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output_image.pixels.foreach_set(pixel_data.ravel())
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output_image.update()
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