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I'm iterating over the material slots in all the meshes in an imported scene, and I'm wondering if there's a way to downsample the image data (using python) associated with the material -- or should I just do it w/the standard python fare (the numpy family). ie I'm assuming blender has some built in bilinear / bicubic downsampling functionality, but I'm new to the API.

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for i, obj in enumerate(meshes):
    for s in obj.material_slots:
        if s.material and s.material.use_nodes:
            for n in s.material.node_tree.nodes:
                if n.type == 'TEX_IMAGE':
                    select_mat = n.image.size[:]
                    print(obj.name,'uses',n.image.name,'saved at',n.image.filepath, select_mat)
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    $\begingroup$ There's image.scale(new_width, new_height). $\endgroup$ Commented Jul 22, 2022 at 4:33
  • $\begingroup$ Seems like a step in the right direction! @scurest does that allow you to specify the filtering? or what does it do? docs are somewhat unclear. $\endgroup$ Commented Jul 22, 2022 at 5:03

1 Answer 1

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I retooled to something like this:

for image in bpy.data.images:
    print(image.size)
    print("scaling n.image", image.size[0], image.size[1])#, "to", nx, ny)
    print(image.name)

    if image.size[0] == 0 or image.size[1] == 0:
        continue
    nx = math.floor(.25 * image.size[0])
    ny = math.floor(.25 * image.size[1])
    print("scaling image", image.size[0], image.size[1], "to", nx, ny)
    image.scale( nx, ny )
    print("new size is:", image.size[0], image.size[1])
    image.pack()

but the question of what downsampling algorithm is applied still remains.

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