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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. |
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| .. | ||
| __init__.py | ||
| image_blend_test.py | ||
| image_blend_workflow_test.py | ||
| image_stitch_test.py | ||
| nodes_math_test.py | ||
| nodes_number_convert_test.py | ||