ausboss
c15c6c9317
The audit compared every node against ComfyUI core and the major packs; this lands its outcomes in one branch. On-node visual editing (the old Codex-pack interaction, rebuilt): - New Load Image + Pad: image loader with whole-edge pad dragging on the node canvas, align-to-multiple rounding, and a megapixel target that rescales the source before padding so the mask seam stays binary. - Pad Image gains the same handle canvas, fed by an execution-time snapshot of its input; wireframe with diagnostic empty states before the first run. Widgets, outputs, and saved workflows unchanged. - Image Crop + Rotate + Pad's compact panel is now a live stage - crop, pad, and rotate handles on the node, one shared implementation with the full-screen editor so the two surfaces cannot drift. Feature gaps closed against the ecosystem: - Crop For Inpaint: target_megapixels, selectable rescale_algorithm (recorded in the stitcher for the paste-back), and extend_* inputs that grow the frame itself for outpainting. - Save Video: format choice - mp4 h264, mp4 h265, webm vp9 with Opus (resampled to 48 kHz); CRF drives all three. - Load Video: every_nth thinning (fps output divides to match) and a max_frames cap that ends the decode early. - LoRA Loader: saved stack templates behind a bar button, and a console warning when a LoRA's base-model family disagrees with the checkpoint. - LM Studio Chat: history in/out for multi-turn chains and a json_schema widget for structured replies. - Drop Shadow: multiply blend and a shadow_mask output. Align Image: offset outputs for un-aligning after sampling. Color Match: first_frame reference mode as a one-node video flicker fix. Removed (backed up in git history): Select Frame Range and the Video Bundle family - core ImageFromBatch and the core VIDEO wire now cover both jobs. Dead NODE_ID module variables cleaned out of every node file. 455 Python tests, 216 JS tests, validate_nodes.py green on 19 node files.
144 lines
6.1 KiB
Python
144 lines
6.1 KiB
Python
"""Offline tests for Align Image and Image Size."""
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from __future__ import annotations
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import sys
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import unittest
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from pathlib import Path
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import torch
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ROOT = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(ROOT))
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if "nodes" in sys.modules and not hasattr(sys.modules["nodes"], "__path__"):
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del sys.modules["nodes"]
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from nodes._align_helpers import ALIGN_MODES, align_image, aligned_size
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from nodes.node_align_image import AusBossAlignImage
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from nodes.node_image_size import AusBossImageSize
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class AlignedSizeTests(unittest.TestCase):
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def test_crop_rounds_down_pad_rounds_up_resize_rounds_nearest(self):
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# 1000 / 16 = 62.5: down 992, up 1008, nearest ties-up 1008.
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self.assertEqual(aligned_size(1000, 1000, 16, "crop"), (992, 992))
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self.assertEqual(aligned_size(1000, 1000, 16, "pad"), (1008, 1008))
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self.assertEqual(aligned_size(1000, 1000, 16, "resize"), (1008, 1008))
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# 1030 is nearer 1024 than 1040.
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self.assertEqual(aligned_size(1030, 500, 16, "resize"), (1024, 496))
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def test_already_aligned_sizes_pass_through_every_mode(self):
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for mode in ALIGN_MODES:
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self.assertEqual(aligned_size(1024, 768, 32, mode), (1024, 768))
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def test_a_side_smaller_than_one_multiple_snaps_up_to_one(self):
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# Nothing can crop below the smallest legal size.
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for mode in ALIGN_MODES:
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self.assertEqual(aligned_size(20, 100, 32, mode)[0], 32, mode)
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def test_multiple_one_changes_nothing(self):
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for mode in ALIGN_MODES:
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self.assertEqual(aligned_size(1013, 777, 1, mode), (1013, 777))
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def test_unknown_mode_raises(self):
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with self.assertRaises(ValueError):
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aligned_size(100, 100, 16, "stretch")
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def ramp(batch: int, height: int, width: int) -> torch.Tensor:
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"""A BHWC batch whose pixel values encode their own x coordinate."""
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xs = torch.arange(width, dtype=torch.float32) / max(1, width - 1)
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return xs.view(1, 1, -1, 1).expand(batch, height, width, 3).clone()
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class AlignImageTests(unittest.TestCase):
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def test_resize_hits_the_nearest_multiple(self):
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out, width, height, ox, oy = align_image(ramp(2, 500, 1000), 16, "resize")
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self.assertEqual((width, height), (1008, 496))
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self.assertEqual(tuple(out.shape), (2, 496, 1008, 3))
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self.assertEqual((ox, oy), (0, 0))
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def test_crop_is_centered_and_lossless_in_the_kept_region(self):
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frames = ramp(1, 100, 100)
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out, width, height, ox, oy = align_image(frames, 32, "crop")
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self.assertEqual((width, height), (96, 96))
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# Center crop of 100 -> 96 drops 2 columns each side.
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self.assertTrue(torch.equal(out, frames[:, 2:98, 2:98, :]))
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# The original's corner now sits 2 px outside the output.
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self.assertEqual((ox, oy), (-2, -2))
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def test_pad_replicates_edges_up_to_the_next_multiple(self):
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frames = ramp(1, 100, 100)
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out, width, height, ox, oy = align_image(frames, 32, "pad")
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self.assertEqual((width, height), (128, 128))
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# 28 extra pixels split 14/14; the original sits centered, untouched.
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self.assertTrue(torch.equal(out[:, 14:114, 14:114, :], frames))
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# The offsets point exactly at where the original landed.
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self.assertEqual((ox, oy), (14, 14))
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self.assertTrue(
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torch.equal(out[:, oy : oy + 100, ox : ox + 100, :], frames)
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)
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# Padding replicates the border, so corners equal the corner pixel.
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self.assertTrue(torch.equal(out[0, 0, 0], frames[0, 0, 0]))
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self.assertTrue(torch.equal(out[0, -1, -1], frames[0, -1, -1]))
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def test_already_aligned_input_is_returned_as_the_same_object(self):
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frames = ramp(1, 64, 128)
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out, width, height, _ox, _oy = align_image(frames, 32, "crop")
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self.assertIs(out, frames)
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self.assertEqual((width, height), (128, 64))
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def test_crop_mode_pads_a_side_it_cannot_crop(self):
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# 20 px wide with multiple 32: crop cannot reach a multiple below,
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# so that side replicate-pads up to exactly one multiple.
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out, width, height, ox, oy = align_image(ramp(1, 100, 20), 32, "crop")
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self.assertEqual((width, height), (32, 96))
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self.assertEqual(tuple(out.shape), (1, 96, 32, 3))
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# Mixed axes: the padded side is positive, the cropped side negative.
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self.assertEqual((ox, oy), (6, -2))
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def test_batch_and_values_survive(self):
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frames = ramp(3, 40, 40)
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out, _w, _h, _ox, _oy = align_image(frames, 16, "pad")
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self.assertEqual(out.shape[0], 3)
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self.assertGreaterEqual(float(out.min()), 0.0)
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self.assertLessEqual(float(out.max()), 1.0)
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def test_rejects_non_bhwc_input(self):
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with self.assertRaises(ValueError):
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align_image(torch.zeros((64, 64, 3)), 16, "resize")
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class AlignImageNodeTests(unittest.TestCase):
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def test_node_returns_image_size_and_offsets(self):
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node = AusBossAlignImage()
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out, width, height, ox, oy = node.align(ramp(1, 100, 100), 32, "pad")
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self.assertEqual((width, height), (128, 128))
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self.assertEqual(tuple(out.shape), (1, 128, 128, 3))
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self.assertEqual((ox, oy), (14, 14))
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for value in (width, height, ox, oy):
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self.assertIsInstance(value, int)
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def test_mode_choices_match_the_helper(self):
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widget = AusBossAlignImage.INPUT_TYPES()["required"]["mode"][0]
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self.assertEqual(tuple(widget), ALIGN_MODES)
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class ImageSizeNodeTests(unittest.TestCase):
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def test_reports_width_height_and_both_edges(self):
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node = AusBossImageSize()
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self.assertEqual(node.measure(torch.zeros((2, 480, 832, 3))), (832, 480, 832, 480))
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self.assertEqual(node.measure(torch.zeros((1, 1080, 608, 3))), (608, 1080, 1080, 608))
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def test_square_images_agree_on_both_edges(self):
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node = AusBossImageSize()
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self.assertEqual(node.measure(torch.zeros((1, 512, 512, 3))), (512, 512, 512, 512))
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def test_rejects_non_bhwc_input(self):
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with self.assertRaises(ValueError):
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AusBossImageSize().measure(torch.zeros((512, 512)))
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if __name__ == "__main__":
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unittest.main()
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