mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-08-10 08:00:32 +02:00
The visible-mark path had grown three copies of one ladder sweep, four
near-identical `detect` arms, and four hand-rolled `footprint_mask` overrides;
mark knowledge sat in five hand-maintained tables across three modules; and the
flagship `all`/`batch` pipeline existed only in cli.py, written twice with
divergent behavior.
Detection is now one measurement. `_ladder_best` replaces the three sweeps,
`_scan`/`_verdict` replace the four arms, and the winning box travels to the
mask on `TextMarkDetection.match_box` instead of being swept a second time.
`detect_both` returns the strict and relaxed verdicts from one scan, which
halves the arbiter's perception cost (260 -> 130 matchTemplate calls on a 2048²
image, verdicts identical field for field). A per-mark demotion goes in the new
`_post_gate` hook, never in a `detect` override -- an override is invisible to
the single-pass path, which is how the RunningHub and Yuanbao anchor gates
briefly stopped applying.
Everything about a mark is now one registry row: product, label regime, the
platform sentence `identify` reports, the metadata signals that confirm it, and
its TC260 producer codes. `identify._VISIBLE_MARK_PLATFORM`, the signal mapping
in `api.visible_provenance`, `_PRODUCT_OF` and the pill veto are derived from
those rows.
`api.remove_all` / `api.remove_batch` are the library form of the `all` and
`batch` commands; the CLI is a wrapper that owns console text and exit codes.
Progress is a `(stage, detail)` pair of stable tokens, so the CLI keys its
wording off structure rather than parsing the library's prose back.
Two intentional behavior changes, both verified against a recorded 811-image
sample of detector verdicts, removal-mask hashes, arbiter decisions and
`identify` reports:
* A TC260 label now relaxes the vendor its `ContentProducer` names rather than
ByteDance's pair on every China-AIGC image. 333 of 811 samples move; on 185
of them the previously relaxed pair was simply the wrong vendor, and the
mark actually present never reached the relaxed gate its own
`provenance_ncc_factor` was calibrated for.
* A confident LibLibAI detection suppresses the Jimeng pill, like every other
TC260 product's mark. It was registered alongside RunningHub and Baidu, both
of which were added to the hand-written veto list, and it was not. 1 sample
moves, and it is exactly the co-firing case.
Nothing else in that record changes: detector verdicts, mask hashes and
`identify` verdicts are byte-identical, and all 200 calibration constants are
untouched.
Also: `aigc_label` and friends plus `extract_c2pa_info` are memoized on
(path, mtime_ns, size) -- size because this package rewrites in place; the
native TC260 container readers route on magic bytes instead of the file
extension, so a mislabeled AVI or FLV is no longer invisible; `identify` shares
one pixel decode between the DWT-DCT and visible stages (TrustMark keeps its own
Pillow decode, which is not substitutable); and the six `stabilize_*` video
wrappers collapse into one policy table.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
258 lines
10 KiB
Python
258 lines
10 KiB
Python
"""Unicode-safe cv2 image IO (issue #17).
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``cv2.imread`` / ``cv2.imwrite`` pass the path to the platform C runtime, which
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on Windows uses the narrow (ANSI) code-page API and therefore fails on paths
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containing non-ASCII characters (Chinese, Cyrillic, ...). The symptom is a
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``can't open/read file`` warning and a ``None`` decode even though the file
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exists.
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These wrappers route through numpy buffers instead: ``np.fromfile`` /
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``ndarray.tofile`` open the path in Python (full Unicode), and
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``cv2.imdecode`` / ``cv2.imencode`` do the codec work. The decoded/encoded
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bytes are byte-for-byte identical to ``imread`` / ``imwrite``. On macOS/Linux
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cv2 already accepts UTF-8 paths, so the wrappers are behavior-neutral there.
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cv2/numpy are imported lazily inside the functions so importing this module
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stays cheap in a bare environment (matching the rest of the package).
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"""
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# cv2 ships no type stubs; mirror the pragma used by the other cv2-using modules.
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# pyright: reportMissingTypeStubs=false, reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false
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from __future__ import annotations
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from pathlib import Path
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from typing import TYPE_CHECKING, Any
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if TYPE_CHECKING:
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from numpy.typing import NDArray
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def imread(path: str | Path, flags: int | None = None) -> NDArray[Any] | None:
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"""Unicode-safe ``cv2.imread`` with a Pillow fallback for HEIC/AVIF.
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``flags`` defaults to ``cv2.IMREAD_COLOR`` (same as ``cv2.imread``). Returns
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``None`` when the file is missing or cannot be decoded, matching ``cv2.imread``
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semantics so existing ``if img is None`` checks keep working.
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OpenCV cannot decode HEIC/AVIF (and some other containers), so when its decode
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returns None we fall back to Pillow (:func:`_pil_read`): AVIF is native in modern
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Pillow, HEIC works when the optional ``pillow-heif`` plugin is installed. This lets
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the pixel path (visible removal) read the same formats the metadata path already
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scans; normal PNG/JPEG/WebP never reach the fallback, so they are unaffected.
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"""
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import cv2
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import numpy as np
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if flags is None:
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flags = cv2.IMREAD_COLOR
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try:
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data = np.fromfile(str(path), dtype=np.uint8)
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except OSError:
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return None
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if data.size == 0:
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return None
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img = cv2.imdecode(data, flags)
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# cv2.imdecode returns None on an undecodable container (HEIC/AVIF); the type stub
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# omits that, hence the ignore.
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if img is not None: # pyright: ignore[reportUnnecessaryComparison]
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return img
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return _pil_read(path, flags)
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_heif_registered = False
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def _pil_read(path: str | Path, flags: int) -> NDArray[Any] | None:
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"""Decode via Pillow (HEIC/AVIF and any other Pillow-readable container) into the
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cv2 layout ``flags`` implies: grayscale, 3-channel BGR, or BGRA when the source has
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alpha and ``IMREAD_UNCHANGED`` was requested. Returns None if Pillow (with the
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optional HEIF plugin) still cannot open it. No EXIF auto-rotation, matching cv2."""
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import cv2
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import numpy as np
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try:
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from PIL import Image
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except Exception:
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return None
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_register_heif()
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try:
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with Image.open(path) as im:
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im.load()
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if flags == cv2.IMREAD_GRAYSCALE:
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return np.asarray(im.convert("L"))
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has_alpha = im.mode in ("RGBA", "LA", "PA") or "transparency" in im.info
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if flags == cv2.IMREAD_UNCHANGED and has_alpha:
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return cv2.cvtColor(np.asarray(im.convert("RGBA")), cv2.COLOR_RGBA2BGRA)
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return cv2.cvtColor(np.asarray(im.convert("RGB")), cv2.COLOR_RGB2BGR)
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except Exception:
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return None
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def load_image_bgr(path: str | Path) -> NDArray[Any]:
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"""Read ``path`` as a BGR ndarray, raising instead of returning ``None``.
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:func:`imread` keeps cv2's ``None``-on-failure contract because the removal paths
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branch on it. Scripts and tests want the opposite -- fail loudly at the read -- so
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they call this. Each vendor engine used to carry its own verbatim copy.
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"""
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image = imread(path)
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if image is None:
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raise FileNotFoundError(f"Failed to read image: {path}")
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return image
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def to_bgr(image: NDArray[Any]) -> NDArray[Any]:
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"""Return a 3-channel BGR view of ``image``, promoting grayscale and BGRA.
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The cv2-based engines (sparkle + the text-mark detectors/localizers) assume a
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3-channel BGR array for their channel reductions (``mean(axis=2)``, the top-hat
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glyph extraction). A 2D grayscale or 4-channel BGRA input -- a real Gemini-app
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export is opaque RGBA -- would otherwise crash or mis-broadcast.
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Centralizes the shape coercion that was inlined across the engines. A 3-channel
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input is returned unchanged (no copy).
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"""
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import cv2
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if image.ndim == 2 or image.shape[2] == 1:
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return cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)
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if image.shape[2] == 4:
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return cv2.cvtColor(image, cv2.COLOR_BGRA2BGR)
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return image
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def _register_heif() -> None:
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"""Register the HEIF+AVIF Pillow opener/saver via libheif (idempotent, best-effort)."""
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global _heif_registered
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if _heif_registered:
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return
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_heif_registered = True
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import contextlib
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with contextlib.suppress(Exception):
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import pillow_heif # pyright: ignore[reportMissingImports]
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pillow_heif.register_heif_opener()
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# Containers cv2 cannot encode -> written via Pillow (pillow-heif).
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_HEIF_WRITE_EXTS = {".heic", ".heif", ".avif"}
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def _encode_params(ext: str) -> list[int]:
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"""cv2 encode params that PRESERVE quality. The removal only touches the mark's
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footprint, so the container re-encode must not degrade the untouched pixels:
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JPEG at quality 100 with 4:4:4 chroma (no subsampling), WebP at max. Lossless
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containers (PNG/BMP/TIFF) need no params. getattr-guarded so an older OpenCV
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build without the chroma/subsampling flags still gets quality 100."""
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import cv2
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if ext in (".jpg", ".jpeg"):
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params = [cv2.IMWRITE_JPEG_QUALITY, 100]
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cq = getattr(cv2, "IMWRITE_JPEG_CHROMA_QUALITY", None)
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if cq is not None:
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params += [cq, 100]
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sf = getattr(cv2, "IMWRITE_JPEG_SAMPLING_FACTOR", None)
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sf444 = getattr(cv2, "IMWRITE_JPEG_SAMPLING_FACTOR_444", None)
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if sf is not None and sf444 is not None:
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params += [sf, sf444]
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return params
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if ext == ".webp":
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# cv2 WebP: quality 1-100 is LOSSY; a value > 100 selects LOSSLESS mode.
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# "work with originals" requires lossless so a mark-removal re-encode does not
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# degrade the untouched pixels the fill composites over (regression: q100
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# round-tripped a random image at maxdiff ~230, q101 at 0).
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return [cv2.IMWRITE_WEBP_QUALITY, 101]
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return []
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def _pil_write(path: str | Path, img: NDArray[Any]) -> bool:
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"""Encode HEIC/AVIF via Pillow (+pillow-heif) at high quality -- cv2 has no encoder
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for them. BGR / BGRA in; returns False if Pillow (with the plugin) cannot save."""
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import cv2
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import numpy as np
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from PIL import Image
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_register_heif()
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if img.ndim == 3 and img.shape[2] == 4:
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arr, mode = cv2.cvtColor(img, cv2.COLOR_BGRA2RGBA), "RGBA"
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else:
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arr, mode = cv2.cvtColor(to_bgr(img), cv2.COLOR_BGR2RGB), "RGB"
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try:
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Image.fromarray(np.ascontiguousarray(arr), mode).save(str(path), quality=100)
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return True
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except Exception:
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return False
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def imwrite(path: str | Path, img: NDArray[Any]) -> bool:
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"""Unicode-safe image write that PRESERVES the input format at max quality.
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Format is taken from the path extension. HEIC/AVIF (which cv2 cannot encode) go
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through Pillow; everything else through cv2 with quality-preserving params (see
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:func:`_encode_params`) so a lossy re-encode of the untouched pixels stays near-
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lossless. Returns ``True`` on success, ``False`` if the codec rejects the image or
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the path cannot be written (matching ``cv2.imwrite``, never raising)."""
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import cv2
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ext = (Path(path).suffix or ".png").lower()
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if ext in _HEIF_WRITE_EXTS:
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return _pil_write(path, img)
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try:
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ok, buf = cv2.imencode(ext, img, _encode_params(ext))
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except cv2.error:
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return False
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if not ok:
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return False
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try:
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buf.tofile(str(path))
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except OSError:
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return False
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return True
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# Container extensions that carry an alpha channel (for read/write-with-alpha).
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ALPHA_FORMATS = {".png", ".webp", ".heic", ".heif", ".avif"}
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def read_bgr_and_alpha(path: str | Path) -> tuple[NDArray[Any] | None, NDArray[Any] | None]:
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"""Read an image preserving its alpha channel separately.
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Returns ``(bgr, alpha)`` where ``alpha`` is a single-channel ndarray when the
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source has transparency, else ``None``. Grayscale inputs are promoted to BGR.
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Returns ``(None, None)`` if the image cannot be decoded.
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"""
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import cv2
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image = imread(path, cv2.IMREAD_UNCHANGED)
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if image is None:
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return None, None
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if image.ndim == 2:
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return cv2.cvtColor(image, cv2.COLOR_GRAY2BGR), None
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if image.shape[2] == 4:
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return image[:, :, :3].copy(), image[:, :, 3].copy()
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return image, None
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def write_bgr_with_alpha(path: str | Path, bgr: NDArray[Any], alpha: NDArray[Any] | None) -> bool:
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"""Write BGR (with optional alpha) to ``path``. Returns ``imwrite``'s success flag.
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When ``alpha`` is provided and the output extension supports it, the original
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alpha plane is rejoined unchanged. The watermark region is NOT made transparent:
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the fill reconstructs real pixels there, so zeroing alpha would punch a
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transparent hole that renders as a white box on any non-transparent viewer
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(issue #30). Preserving the input alpha keeps genuinely transparent backgrounds
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intact without inventing new holes.
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Returning the flag is load-bearing: :func:`imwrite` is contractually non-raising, so
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this is the ONLY signal a caller gets that the file was not created. Discarding it let
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a failed write (read-only directory, full disk) run on to ``output.stat()`` and die
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with a bare ``FileNotFoundError`` traceback instead of a readable error.
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Regression: ``tests/test_cli_robustness.py::TestFailedWriteIsReported``.
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"""
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import numpy as np
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if alpha is None or Path(path).suffix.lower() not in ALPHA_FORMATS:
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return imwrite(path, bgr)
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return imwrite(path, np.dstack([bgr, alpha]))
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