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https://github.com/comfyanonymous/ComfyUI.git
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ae88cd1966
Address review feedback: the previous fix allowed ImageBlend to return tensors with > 4 channels (e.g. blending a 3-channel and a 5-channel image produced a 5-channel tensor). This shifted the original failure from blend-time to save/preview-time, because SaveImage and PreviewImage both call PIL.Image.fromarray, which only supports 1/3/4-channel arrays. Fix: - In Blend.execute, the alignment target is now min(max(c1, c2), 4): any image with more than 4 channels is truncated, any image with fewer is padded with 1.0s up to the (capped) target. This makes the RGB/RGBA case work and also makes the >4-channel case work end-to-end rather than just deferring its failure. - Update the regression test that previously codified the wrong 5-channel-output behavior to assert the correct 4-channel cap. - Add test_output_capped_at_four_channels (both inputs > 4 channels). - Add test_save_compatible_output_passes_through_pil that mirrors SaveImage's exact PIL.Image.fromarray conversion to catch regressions in the save/preview path. - Add a small workflow-validation test (image_blend_workflow_test.py) that loads tests/inference/graphs/image_blend_channel_mismatch.json and verifies its node types and wiring, so the demo workflow can't silently bitrot. Verified end-to-end against a local ComfyUI server: the workflow runs, output is RGBA, downstream SaveImage succeeds.
57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
import json
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import pathlib
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WORKFLOW_PATH = (
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pathlib.Path(__file__).resolve().parents[2]
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/ "tests"
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/ "inference"
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/ "graphs"
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/ "image_blend_channel_mismatch.json"
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)
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def test_workflow_loads():
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with open(WORKFLOW_PATH) as f:
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graph = json.load(f)
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assert isinstance(graph, dict) and graph, "workflow JSON is empty"
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def test_workflow_uses_expected_node_types():
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"""The workflow uses a fixed, minimal set of nodes. If any are renamed
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or removed upstream, this test fails fast instead of letting the demo
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bitrot silently."""
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expected = {
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"EmptyImage",
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"SolidMask",
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"JoinImageWithAlpha",
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"ImageBlend",
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"SaveImage",
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}
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with open(WORKFLOW_PATH) as f:
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graph = json.load(f)
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actual = {node["class_type"] for node in graph.values()}
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assert expected.issubset(actual), (
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f"workflow is missing required node types: {expected - actual}"
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)
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def test_workflow_exercises_imageblend_with_mismatched_channels():
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"""Sanity-check that the workflow actually wires an RGB output and an
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RGBA output into ImageBlend (the CORE-103 case). If someone edits the
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JSON and accidentally breaks this guarantee, the demo loses its point."""
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with open(WORKFLOW_PATH) as f:
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graph = json.load(f)
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blend_nodes = [n for n in graph.values() if n["class_type"] == "ImageBlend"]
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assert len(blend_nodes) == 1, "expected exactly one ImageBlend node"
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blend = blend_nodes[0]
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src1_id, _ = blend["inputs"]["image1"]
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src2_id, _ = blend["inputs"]["image2"]
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types = {graph[src1_id]["class_type"], graph[src2_id]["class_type"]}
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assert "JoinImageWithAlpha" in types, (
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"workflow no longer feeds an RGBA image into ImageBlend"
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)
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assert "EmptyImage" in types, (
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"workflow no longer feeds a plain RGB image into ImageBlend"
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)
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