73 lines
2.8 KiB
Python
73 lines
2.8 KiB
Python
"""Regression tests for ImageCompositor's handling of untrusted layer state.
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The compositor's `compositor` widget value is persisted into the saved workflow
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and is accepted verbatim on `POST /prompt`, so every field in it is untrusted
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input, not an internal invariant.
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"""
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import numpy as np
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import pytest
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import torch
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from comfy_extras.nodes_compositor import (
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_layer_params,
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composite_from_state,
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expand_item_frames,
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state_from_items,
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)
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def _solid(color, w=4, h=4) -> torch.Tensor:
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frame = np.zeros((h, w, len(color)), dtype=np.float32)
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frame[:] = color
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return torch.from_numpy(frame).unsqueeze(0)
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class TestLayerOpacity:
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@pytest.mark.parametrize(
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("raw", "expected"),
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[(-0.5, 0.0), (0.0, 0.0), (0.25, 0.25), (1.0, 1.0), (3.0, 1.0)],
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)
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def test_opacity_is_clamped(self, raw, expected):
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assert _layer_params({"opacity": raw}, 4, 4)["opacity"] == expected
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def test_opacity_defaults_to_opaque(self):
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assert _layer_params({}, 4, 4)["opacity"] == 1.0
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def test_out_of_range_opacity_does_not_leak_into_the_next_layer(self):
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# The canvas is only clamped once, after every layer has been composited,
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# so an out-of-range coverage multiplier on one layer changes the *blend*
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# of the layer above it. White at opacity 3.0 over black leaves the canvas
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# at 3.0; the multiply above it then reads 3.0 as its backdrop and the
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# result is visibly lighter than the same stack at opacity 1.0.
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def run(opacity):
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state = {
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"canvas": (2, 2),
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"layers": [{"opacity": opacity}, {"opacity": 1.0, "blend": "multiply"}],
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"inputs": None,
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"background": {"color": "#000000", "opacity": 1.0, "visible": True},
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"order": None,
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}
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tensors = [_solid([1.0, 1.0, 1.0], 2, 2), _solid([0.5, 0.5, 0.5], 2, 2)]
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return composite_from_state(tensors, state, [None, None])[0, 0, 0, :3]
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assert run(3.0).tolist() == pytest.approx(run(1.0).tolist(), abs=1e-6)
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class TestGraphOnlyBackground:
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def test_default_layout_background_is_hidden(self):
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# A visible white background here would make every graph-only run emit a
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# white matte instead of transparency.
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frames = expand_item_frames([{"image": _solid([1.0, 0.0, 0.0])}])
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state = state_from_items(frames, (4, 4))
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assert state["background"]["visible"] is False
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def test_uncovered_canvas_stays_transparent(self):
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tensors = [_solid([1.0, 0.0, 0.0], w=2, h=2)]
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frames = expand_item_frames([{"image": tensors[0]}])
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state = state_from_items(frames, (4, 4))
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out = composite_from_state(tensors, state, [None])[0]
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assert out.shape[-1] == 4
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assert float(out[0, 0, 3]) == pytest.approx(1.0)
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assert float(out[3, 3, 3]) == pytest.approx(0.0)
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