283 lines
12 KiB
Python
283 lines
12 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""Diffusion ControlNet support: family-gated discovery of ControlNet models, resolution to
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a loadable diffusers repo/dir, control-image preprocessing, and a capability gate.
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Mirrors ``diffusion_lora.py``. Two differences from LoRA: (1) a ControlNet is a full diffusers
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repo (loaded via ``from_pretrained``), not a single-file adapter, so resolution yields a repo id
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or local directory rather than a file path; (2) ControlNet needs a spatial *control image*, which
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is either supplied already-preprocessed ("passthrough", as in ComfyUI where preprocessing is a
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separate step) or derived here ("canny", a dependency-free edge map).
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ControlNet models are architecture-specific (a FLUX ControlNet cannot drive a Qwen base), so
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discovery is family-gated exactly like the LoRA picker. The request never carries a filesystem
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path -- only a discovery id or a public ``owner/name`` repo id -- so a client cannot make the
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backend read an arbitrary location.
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"""
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from __future__ import annotations
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import re
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any, Optional
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from utils.paths.storage_roots import studio_root
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# Control map types. "passthrough": the supplied image IS the control map (a depth/pose/etc.
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# map produced elsewhere). "canny": derive an edge map here (no heavy detector dependency).
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CONTROL_TYPES = ("passthrough", "canny")
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# Families whose diffusers pipeline supports ControlNet (declared in diffusion_families via
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# controlnet_pipeline_class). Native sd.cpp ControlNet is a follow-up. Torchao fp8/int8 dense
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# and GGUF-via-diffusers are gated off, same rule as LoRA.
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_DIFFUSERS_BLOCKED_QUANT = ("int8", "fp8", "nvfp4", "mxfp8")
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@dataclass(frozen = True)
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class ControlNetCatalogEntry:
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"""One discoverable ControlNet model."""
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id: str
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display_name: str
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source: str # "local" | "hub"
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families: tuple[str, ...] = () # compatible family names (empty = shown, not gated)
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repo_id: Optional[str] = None # for source == "hub"
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local_path: Optional[str] = None # for source == "local"
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control_types: tuple[str, ...] = ("passthrough",) # recommended control types
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is_union: bool = False # a single model covering many control modes
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@dataclass(frozen = True)
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class ResolvedControlNet:
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"""A ControlNet resolved to something ``from_pretrained`` can load."""
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id: str
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path: str # repo id (hub) or local directory
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is_local: bool
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# Curated, family-tagged catalog. Union models (one model, many control modes) dominate real
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# usage, so they are the default picks. Extend as more are curated; local dirs + a bare public
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# ``owner/name`` repo id also work.
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_CURATED: tuple[ControlNetCatalogEntry, ...] = (
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ControlNetCatalogEntry(
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id = "flux-union-pro",
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display_name = "FLUX.1 ControlNet Union Pro (Shakker-Labs)",
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source = "hub",
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families = ("flux.1",),
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repo_id = "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro",
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control_types = ("canny", "depth", "pose", "passthrough"),
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is_union = True,
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),
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ControlNetCatalogEntry(
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id = "qwen-union",
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display_name = "Qwen-Image ControlNet Union (InstantX)",
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source = "hub",
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families = ("qwen-image",),
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repo_id = "InstantX/Qwen-Image-ControlNet-Union",
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control_types = ("canny", "depth", "pose", "passthrough"),
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is_union = True,
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),
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)
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def controlnets_dir() -> Path:
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"""Local directory Studio scans for user-provided ControlNet model folders."""
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d = studio_root() / "controlnets" / "diffusion"
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d.mkdir(parents = True, exist_ok = True)
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return d
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def sanitize_id(raw: str) -> str:
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"""Filesystem-safe id from a repo id / folder name."""
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stem = raw.rsplit("/", 1)[-1]
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stem = re.sub(r"[^A-Za-z0-9._-]+", "_", stem).strip("._-")
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return stem or "controlnet"
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def _has_controlnet_weights(p: Path) -> bool:
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"""True when ``p`` holds a loadable diffusers ControlNet weight (or shard index).
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A config-only folder (interrupted copy/download) would otherwise be advertised and
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then fail deep inside ``from_pretrained`` as a generic 500. Accept the standard
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single-file weights, a sharded weight index, or any ``.safetensors`` shard."""
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names = (
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"diffusion_pytorch_model.safetensors",
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"diffusion_pytorch_model.bin",
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"diffusion_pytorch_model.safetensors.index.json",
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"diffusion_pytorch_model.bin.index.json",
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)
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if any((p / n).exists() for n in names):
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return True
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try:
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return any(child.suffix == ".safetensors" for child in p.iterdir())
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except OSError:
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return False
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def _scan_local() -> list[ControlNetCatalogEntry]:
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"""A local ControlNet is a directory containing a diffusers config + weights."""
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entries: list[ControlNetCatalogEntry] = []
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root = controlnets_dir()
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try:
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children = sorted(root.iterdir())
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except OSError:
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return entries
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for p in children:
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if not p.is_dir():
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continue
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# Require BOTH the config and a loadable weight/index: a config-only folder is an
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# incomplete copy/download, and advertising it would fail later in from_pretrained.
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if not (p / "config.json").exists() or not _has_controlnet_weights(p):
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continue
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entries.append(
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ControlNetCatalogEntry(
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id = p.name,
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display_name = p.name,
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source = "local",
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local_path = str(p),
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control_types = CONTROL_TYPES,
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)
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)
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return entries
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def list_controlnets(*, family: Optional[str] = None) -> list[ControlNetCatalogEntry]:
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"""Merged catalog (curated + local), optionally family-filtered. Cheap: one dir scan
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plus the in-memory curated list. Network is only touched on resolve()."""
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merged = list(_CURATED) + _scan_local()
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if family:
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fam = family.strip().lower()
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merged = [e for e in merged if not e.families or fam in {f.lower() for f in e.families}]
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merged.sort(key = lambda e: (e.source != "local", e.display_name.lower()))
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return merged
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def _catalog_by_id() -> dict[str, ControlNetCatalogEntry]:
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return {e.id: e for e in (list(_CURATED) + _scan_local())}
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def resolve_controlnet(spec_id: str, *, family: Optional[str] = None) -> ResolvedControlNet:
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"""Resolve a ControlNet id to a loadable repo id / local dir.
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Accepts a catalog/local id, or a bare public HF repo id (``owner/name``). The backend
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loads the result with ``ControlNetModelClass.from_pretrained(path)`` (download + cache
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handled there, like the base pipeline). Raises on an unknown id -> the caller maps to 400.
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``family`` (the loaded base family) enforces catalog compatibility: a ControlNet is
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architecture-specific, so a catalog entry tagged for another family is rejected here
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with a clear error rather than being loaded through the wrong pipeline class later.
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"""
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entry = _catalog_by_id().get(spec_id)
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if entry is not None:
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# A curated/local entry may declare the families it is built for. A client that
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# bypasses the UI filter (direct API call) could send an entry for another family;
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# reject it before any download so it never reaches the wrong ControlNet pipeline.
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fam = (family or "").strip().lower()
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if entry.families and fam and fam not in {f.lower() for f in entry.families}:
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raise ValueError(
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f"ControlNet '{spec_id}' is for {', '.join(entry.families)}, not the loaded "
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f"'{family}' model; pick a ControlNet built for this family."
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)
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if entry.source == "local":
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path = entry.local_path or ""
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if not path or not Path(path).is_dir():
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raise FileNotFoundError(f"ControlNet '{spec_id}' is no longer present on disk")
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return ResolvedControlNet(spec_id, path, is_local = True)
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if not entry.repo_id:
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raise ValueError(f"ControlNet '{spec_id}' has no repo")
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return ResolvedControlNet(spec_id, entry.repo_id, is_local = False)
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# A bare public HF repo id (owner/name). STRICT shape -- exactly one slash and
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# alphanumeric-leading segments -- so a filesystem-looking id (/tmp/x, ../x, ~/x,
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# C:\x) can never reach from_pretrained, which would happily treat it as a local
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# directory and bypass the controlnets_dir() no-raw-path contract.
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if re.fullmatch(r"[A-Za-z0-9][A-Za-z0-9_.-]*/[A-Za-z0-9][A-Za-z0-9_.-]*", spec_id):
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return ResolvedControlNet(spec_id, spec_id, is_local = False)
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raise FileNotFoundError(
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f"unknown ControlNet '{spec_id}': not a local model, catalog entry, or HF repo id"
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)
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# Union ControlNet mode indices. A single "union" model covers several control modes and
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# selects the active one via an integer ``control_mode`` argument; these are the standard
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# indices used by the FLUX.1 / Qwen-Image union ControlNets. "passthrough" (an already-made
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# map) carries no intrinsic mode, so union_control_mode() defaults it to 0 (a union model
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# still requires a concrete mode).
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_UNION_CONTROL_MODES: dict[str, int] = {
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"canny": 0,
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"tile": 1,
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"depth": 2,
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"blur": 3,
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"pose": 4,
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"gray": 5,
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"lq": 6,
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}
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def union_control_mode(spec_id: str, control_type: str) -> Optional[int]:
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"""The integer ``control_mode`` for a union ControlNet, or None.
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A union model REQUIRES a concrete ``control_mode`` (diffusers raises when it is None),
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so for a curated union entry always return an index: the mapped mode, or a default
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(0 / canny) for a type that carries no intrinsic mode such as 'passthrough' (an
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already-made control map, which is also the UI's default for these models). For a
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non-union entry return None so the caller omits the kwarg (it has a single fixed
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mode). Pure lookup, no network."""
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entry = _catalog_by_id().get(spec_id)
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if entry is None or not entry.is_union:
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return None
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return _UNION_CONTROL_MODES.get((control_type or "").strip().lower(), 0)
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def preprocess_control(image: Any, control_type: str) -> Any:
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"""Turn a source image into a control map.
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``passthrough`` returns the image unchanged (it is already a depth/pose/edge map made
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elsewhere). ``canny`` derives a dependency-free gradient edge map (a rough stand-in for a
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true Canny; a cv2/kornia detector and depth/pose detectors are a follow-up). Unknown types
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pass through so a new type never hard-fails generation.
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"""
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ct = (control_type or "passthrough").strip().lower()
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if ct != "canny":
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return image
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import numpy as np
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from PIL import Image
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gray = np.asarray(image.convert("L"), dtype = np.float32)
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gy, gx = np.gradient(gray)
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mag = np.hypot(gx, gy)
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peak = float(mag.max())
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if peak <= 1e-6:
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return image # flat image -> nothing to trace; don't emit a black map
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mag = mag / peak * 255.0
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edges = (mag > 40.0).astype(np.uint8) * 255 # white edges on black, the ControlNet convention
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return Image.fromarray(edges).convert("RGB")
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def supports_controlnet(
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*,
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engine: str,
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family: Optional[str],
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has_controlnet_pipeline: bool,
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model_kind: Optional[str],
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transformer_quant: Optional[str],
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) -> bool:
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"""Whether the loaded model can apply a ControlNet.
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diffusers only for now (native sd.cpp is a follow-up). Requires the family to declare a
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ControlNet pipeline. Blocked for the diffusers GGUF path and torchao fp8/int8 dense
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(same constraints as LoRA): those transformers cannot host the extra conditioning cleanly.
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"""
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if not family or not has_controlnet_pipeline:
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return False
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if engine != "diffusers":
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return False
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if model_kind == "gguf":
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return False
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if transformer_quant and str(transformer_quant).strip().lower() in _DIFFUSERS_BLOCKED_QUANT:
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return False
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return True
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