Jet Huang
7b522fdb58
ColorLab (all new inputs optional; defaults reproduce v1.6.0, checked against a
golden made from the v1.6.0 code):
- tone_engine=local: edge-aware Highlights/Shadows (local Laplacian), Clarity
(guided band), dark-channel Dehaze, endpoint-preserving Contrast; GPU when
available.
- wb_temperature / wb_tint; second output params_json (non-default settings);
params_json input adds onto the sliders.
- params_json-only settings for presets: point curves (master + RGB), camera
calibration, grain, post-crop vignette, B&W magenta mixer.
New nodes:
- "Color: Apply ColorLab Preset": image + params_json + strength (+ mask).
- "Color: Lightroom Preset (XMP)": reads .xmp and .lrtemplate (Lua read as data
only) from models/lightroom_presets, maps crs: settings to ColorLab (incl.
parametric curve, calibration, Kelvin white balance against as-shot) and
reports what is not supported; outputs image, params_json and report.
- "Color: Lightroom Preset Contact Sheet": labelled grid of a collection.
Preset library: collections (All, Favorites, Recent, sub-folders), favourites and
recents in .jh_presets.json, CPU thumbnails on the node's last image with an LRU
cache, served by /jh_pixelpro/lr/{presets,thumb,favorite} (listed names only).
105 lines
3.7 KiB
Python
105 lines
3.7 KiB
Python
from __future__ import annotations
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import importlib.util
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import json
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import sys
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from pathlib import Path
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import pytest
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import torch
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_PACK_ROOT = Path(__file__).resolve().parent.parent
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_PACK_MODULE_NAME = "comfyui_jh_pixelpro_under_test_lr_preset"
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XMP = _PACK_ROOT / "tests" / "fixtures" / "lr" / "warm-film.xmp"
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def _load_pack():
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if _PACK_MODULE_NAME in sys.modules:
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return sys.modules[_PACK_MODULE_NAME]
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spec = importlib.util.spec_from_file_location(
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_PACK_MODULE_NAME,
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_PACK_ROOT / "__init__.py",
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submodule_search_locations=[str(_PACK_ROOT)],
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)
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module = importlib.util.module_from_spec(spec)
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sys.modules[_PACK_MODULE_NAME] = module
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spec.loader.exec_module(module)
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return module
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def _run(node, *args, **kwargs):
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return node.apply(*args, **kwargs)["result"]
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@pytest.fixture(scope="module")
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def node_cls():
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return _load_pack().NODE_CLASS_MAPPINGS["JHPixelProLightroomPreset"]
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def _image() -> torch.Tensor:
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torch.manual_seed(5)
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return torch.rand(1, 32, 48, 3)
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def test_registered_and_simple(node_cls) -> None:
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pack = _load_pack()
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assert (
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pack.NODE_DISPLAY_NAME_MAPPINGS["JHPixelProLightroomPreset"]
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== "Color: Lightroom Preset (XMP)"
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)
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assert node_cls.RETURN_NAMES == ("image", "params_json", "report")
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spec = node_cls.INPUT_TYPES()
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assert list(spec["required"]) == ["image", "preset", "strength"]
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assert spec["optional"]["tone_engine"][1]["default"] == "local"
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def test_apply_from_path(node_cls) -> None:
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image = _image()
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out, params_json, report = _run(
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node_cls(), image, "(no presets found)", 1.0, preset_path=str(XMP)
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)
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assert out.shape == image.shape and not torch.allclose(out, image)
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params = json.loads(params_json)
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assert params["tone_engine"] == "local"
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assert params["basic_exposure"] == pytest.approx(0.35)
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assert params["tone_curve"][0] == [0.0, 18.0]
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assert "JH Warm Film" in report and "Vintage 06" in report
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def test_params_json_reproduces_image_in_colorlab_and_apply(node_cls) -> None:
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pack = _load_pack()
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image = _image()
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out, params_json, _ = _run(node_cls(), image, "x", 1.0, preset_path=str(XMP))
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apply = pack.NODE_CLASS_MAPPINGS["JHPixelProColorLabApply"]()
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again, _ = apply.apply(image, params_json, 1.0)
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assert torch.allclose(out, again, atol=1e-6)
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colorlab = pack.NODE_CLASS_MAPPINGS["JHPixelProColorLab"]
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spec = colorlab.INPUT_TYPES()
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sliders = {k: v[1]["default"] for k, v in spec["required"].items() if k != "image"}
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sliders.update({k: v[1]["default"] for k, v in spec["optional"].items() if "default" in v[1]})
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via_colorlab, chained = colorlab().apply(image, params_json=params_json, **sliders)
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assert torch.allclose(out, via_colorlab, atol=1e-6)
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assert json.loads(chained)["tone_curve"] == json.loads(params_json)["tone_curve"]
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def test_strength_and_mask(node_cls) -> None:
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image = _image()
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same, half_json, _ = _run(node_cls(), image, "x", 0.0, preset_path=str(XMP))
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assert torch.equal(same, image)
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_, half_json, _ = _run(node_cls(), image, "x", 0.5, preset_path=str(XMP))
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assert json.loads(half_json)["basic_exposure"] == pytest.approx(0.175)
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mask = torch.zeros(1, 32, 48)
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mask[:, :, :24] = 1.0
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out, _, _ = _run(node_cls(), image, "x", 1.0, preset_path=str(XMP), mask=mask)
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assert torch.allclose(out[:, :, 24:], image[:, :, 24:])
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def test_missing_preset_explains_where(node_cls) -> None:
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with pytest.raises(ValueError, match="lightroom_presets"):
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_run(node_cls(), _image(), "(no presets found)", 1.0)
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def test_is_changed_tracks_file(node_cls) -> None:
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key = node_cls.IS_CHANGED("x", preset_path=str(XMP))
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assert str(XMP) in key and key.split(":")[-1].isdigit()
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