Sync conda recipe with v0.20.0

docs/release-and-distribution.md

@@ -52,6 +52,13 @@ If a distribution job fails because a repository or Hugging Face credential is
 invalid, rotate the corresponding GitHub secret and rerun the failed job. A
 manual Homebrew formula update is the fallback when its automation is blocked.
 
+After PyPI publication, update `packaging/conda/recipe.yaml` to the released
+version and the SHA-256 of the published source distribution. Use the published
+artifact rather than a locally built archive as the hash source. Keep the
+recipe's runtime dependencies aligned with the core dependencies in
+`pyproject.toml`; document any conda-forge package that is unavailable and must
+be omitted.
+
 ## Source distribution boundary
 
 The wheel includes the package under `src/`.
@@ -69,7 +76,6 @@ The package uses hatchling through the unpinned `hatchling` build requirement in
 ## Other channels
 
 The repository includes a conda recipe under `packaging/conda/recipe.yaml`.
-Keep its runtime dependencies aligned with `pyproject.toml`.
 
 The ComfyUI nodes are maintained and versioned separately from this package.
 A library release does not by itself publish a new ComfyUI node version.
@@ -82,4 +88,6 @@ After publication, verify:
 - the package version matches the tag;
 - the Homebrew formula points to the new source distribution;
 - the distribution workflow completed successfully;
+- the repository's conda recipe matches the published version and source
+  distribution;
 - a clean install can run `remove-ai-watermarks --version`.

packaging/conda/recipe.yaml

@@ -1,7 +1,7 @@
 schema_version: 1
 
 context:
-  version: "0.10.1"
+  version: "0.20.0"
   python_min: "3.10"
 
 package:
@@ -10,7 +10,7 @@ package:
 
 source:
   url: https://pypi.org/packages/source/r/remove-ai-watermarks/remove_ai_watermarks-${{ version }}.tar.gz
-  sha256: ec92b450363d947cd897f0b75c18e75c2988ff79314ea247333ba892470b5a77
+  sha256: 28eb7aaeace7cfa50fe158ed6da72a4afa526d4be11e9f9c614b90edbaccf0b4
 
 build:
   noarch: python
@@ -25,11 +25,15 @@ requirements:
   run:
     - python >=${{ python_min }}
     - pillow >=10.0.0
+    - pillow-heif >=0.13.0
     - piexif >=1.1.3
     - numpy >=1.24.0
     - py-opencv >=4.8.0
     - click >=8.0.0
     - python-dotenv >=1.0.0
+    # c2pa-python is a core PyPI dependency but is not packaged on conda-forge.
+    # The guarded import falls back to the built-in C2PA byte scanner when it is
+    # absent. Add it here once a c2pa-python feedstock exists.
 
 tests:
   - python:
@@ -48,12 +52,11 @@ about:
   homepage: https://github.com/wiltodelta/remove-ai-watermarks
   summary: Remove visible and invisible AI watermarks from images
   description: |
-    Detect and remove visible AI watermarks (Gemini / Nano Banana sparkle,
-    ByteDance Doubao and Jimeng, Samsung Galaxy AI) and strip AI-provenance
-    metadata (C2PA, EXIF, IPTC, PNG text chunks) from images. The core package
-    covers the identify / metadata / visible / erase command surface; optional
-    pip extras add SynthID diffusion removal and additional invisible-watermark
-    detectors.
+    Detect and remove registered visible AI-provenance marks and strip
+    AI-provenance metadata (C2PA, EXIF, IPTC, and PNG text chunks) from images.
+    The core package covers the identify, metadata, visible, and erase command
+    surface. Optional pip extras add SynthID diffusion removal and additional
+    invisible-watermark detectors.
   license: Apache-2.0
   license_file: LICENSE
   repository: https://github.com/wiltodelta/remove-ai-watermarks