digital-garbageandClaude Opus 5
74671329f9
[Log] Info: FunPack Diffusion Model Loader | flux.safetensors loaded, attention sage
[Log] Alert: MiniMaxH3ImageToVideo node | no "first_image" input is connected
[Log] Warning: FunPack LoRA Loader | style.safetensors is empty and will not load
[Log] Critical: torch | cannot allocate 14 GB (3 GB free); the run will not start
The difference between the middle two is the one that matters. Alert is a
choice you may not have made on purpose. Warning is something that will NOT
do what its name says -- the level v4 needed and did not have, which is how
560 handlers came to swallow a failure and carry on, so a feature could be
switched on, do nothing, and never say so.
Info is not decoration either: "loaded on GPU using sage attention" is how
an attention setting that did nothing gets noticed months before the
pictures look wrong enough to investigate.
Every call site moved -- there is no note() left to be vague through -- and
the loaders now say what they actually loaded rather than only what they
were asked for. Records are kept in a bounded ring as well as printed, so a
long rental session cannot turn the log into a memory leak, and served at
/funpack/api/log so a person can read it somewhere other than a terminal
full of ComfyUI's own output. There is a page for it.
Also dropped the preflight this was traded for: min and max are already
declared and already enforced at both doors, and a second protection layer
around a check that exists is ceremony.
Two mistakes worth keeping: a log line reached into the model's shape to
describe it and could have failed the load it was only narrating; and both
new pages passed `children` to an element that takes `rows`, which the kit
accepted and silently dropped. It throws on an unknown element and not on an
unknown prop.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
102 lines
4.2 KiB
Python
102 lines
4.2 KiB
Python
"""Detail: sharpen or soften what the model is producing, while it produces it.
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Declares NO traits, so it applies to every model -- image, video, anything that
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ships later. That is the other half of the compatibility rule: ALG narrows itself
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to models with a time axis, and this narrows itself to nothing.
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It is also the modifier that can be SEEN on a laptop. Ratings, anchors and audio
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clocks all need hardware or history before they mean anything; this changes the
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picture on a 512x512 image in ten seconds, so "the setting did what it said" is
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something to look at rather than infer.
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The maths is ComfyUI's own `LatentOperationSharpen`, not a copy of it. The
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technique here is FunPack's -- v4 measured this and settled on it -- but the
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kernel is core's, tested by core, and a second implementation of a gaussian
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unsharp mask would only be a second thing to keep correct.
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"""
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from ..._core import log, patching
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ID = "sharpen"
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TITLE = "Detail"
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MOUNT = "generation.sampling"
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STAGE = "sampling"
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STATUS = "proven"
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SETTINGS = {
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"enabled": {
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"type": "bool", "default": False,
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"label": "Adjust detail",
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"hint": "Sharpens or softens as the picture forms, not afterwards.",
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},
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# Range set from measurement, not from what looked like a round number:
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# 0.4 gives a visibly richer picture on SD1.5 that still reads correctly,
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# and 1.2 already blows out the highlights and smears the subject. A slider
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# whose top half destroys the image is a slider that lies about its range.
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"amount": {
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"type": "float", "default": 0.4, "min": -1.0, "max": 1.0, "step": 0.05,
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"label": "Amount", "ui": "slider",
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"hint": "Above zero sharpens, below zero softens.",
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"when": {"enabled": True},
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},
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"radius": {
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"type": "int", "default": 5, "min": 1, "max": 31, "step": 2,
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"label": "Spread", "ui": "slider",
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"hint": "How far the effect reaches from each detail.",
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"when": {"enabled": True},
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},
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}
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def _operation(radius, amount):
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"""Core's sharpen kernel, asked for by name rather than reimplemented.
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`nodes_post_processing` is imported FIRST on purpose. ComfyUI has a genuine
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cycle between it and `nodes_latent` -- each imports from the other -- which
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resolves only because init_extra_nodes happens to reach post_processing
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first. Importing nodes_latent on its own raises ImportError, so a custom
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node that reaches for it has to break the cycle the same way.
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"""
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import comfy_extras.nodes_post_processing # noqa: F401 (breaks the cycle)
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from comfy_extras.nodes_latent import LatentOperationSharpen
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return LatentOperationSharpen.execute(
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sharpen_radius=int(radius), sigma=1.0, alpha=float(amount)).result[0]
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def install(patcher, values, key):
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if not values.get("enabled"):
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return None
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amount = float(values.get("amount", 0.4))
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if amount == 0.0:
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# Zero is a request for nothing, and saying so beats reporting that a
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# modifier ran when it could not have changed a single pixel.
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log.alert("FunPack Detail", "enabled at amount 0, which changes nothing")
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return None
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radius = int(values.get("radius", 5))
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operation = _operation(radius, abs(amount))
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sharpening = amount > 0
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def pre_cfg(args):
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conds_out = args["conds_out"]
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# Applied to the guidance DIFFERENCE when there is one, exactly as
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# core's LatentApplyOperationCFG does -- operating on the raw
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# conditioned output instead would fight the guidance rather than
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# shape it.
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if len(conds_out) == 2:
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adjusted = operation(latent=(conds_out[0] - conds_out[1]))
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changed = adjusted + conds_out[1]
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else:
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changed = operation(latent=conds_out[0])
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conds_out[0] = changed if sharpening else (2 * conds_out[0] - changed)
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return conds_out
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# Tagged, because this hook is an anonymous entry in a list: without a
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# mark there is nothing to identify it by when it has to come off again.
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patcher.set_model_sampler_pre_cfg_function(patching.tag(pre_cfg, key))
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return f"{'sharpening' if sharpening else 'softening'} by {abs(amount)} at spread {radius}"
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PROVIDES = {"modifier": install}
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