Local SDXL run on a Gemini 3 Pro output (snowboard scene, 2816x1536), seed 42,
strength 0.05, steps 50, ~10 min on MPS. Gemini app's "Verify with SynthID"
returned "no SynthID watermark detected" on the cleaned file. This closes the
verification gap noted in v0.4.0 release notes and confirms architectural
equivalence to the raiw-app production fal-ai/fast-sdxl path.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- Bump diffusers minimum to 0.38.0 (closes GHSA-98h9-4798-4q5v).
- Refresh uv.lock to pull urllib3 2.7.0 (closes GHSA-qccp-gfcp-xxvc and
GHSA-mf9v-mfxr-j63j via transitive update from requests / huggingface-hub).
- Allow pre-releases globally (`[tool.uv] prerelease = "allow"`) because
diffusers 0.38.0 declares a dependency on safetensors>=0.8.0rc0. Drop
once safetensors 0.8.0 stable is published or diffusers re-pins.
uv-secure --ignore-unfixed now reports zero vulnerabilities.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
SD-1.5 dreamshaper at 768 px did not defeat SynthID v2 on Gemini 3 Pro
outputs (verified May 2026 via Gemini app's "Verify with SynthID"). Switch
the default invisible engine to SDXL at 1024 px, matching the raiw-app
production config (strength 0.05, steps 50). Drop the SD-1.5 pipeline.
Metadata layer: add C2PA UUID and IPTC AI marker byte-scan detection
across all formats, plus an ISOBMFF box walker (noai/isobmff.py) that
strips top-level C2PA uuid and JUMBF jumb boxes from AVIF/HEIF/JPEG-XL
containers without re-encoding.
README gets a Legal table and a Threat-model section about SynthID v2's
136-bit payload. CLAUDE.md tracks the SD-1.5 regression as historical
context.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Reverse alpha blending applied at the assumed default position painted
a visible inverse-sparkle artifact onto clean or edited images. The
function now returns an unmodified copy when detection fails, instead
of falling back to the hardcoded Gemini corner. Bump to 0.3.5.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- metadata --check now shows claim_generator, c2pa_spec, digital_source_type,
c2pa_actions, signer instead of empty table for C2PA-only files
- reuses existing extract_c2pa_chunk() from noai/c2pa.py — no more duplicate
PNG chunk parsing or full-file reads
- adds data/samples/openai-images-2/amur-leopard.png: real gpt-image-2 output
with C2PA manifest signed by OpenAI OpCo LLC / Trufo CA (spec 2.2.0)
- removes stale data/samples/nano-banana-1/2.png (no longer referenced)
- updates README: new Images 2.0 row in supported models table
- documents known text-degradation limitation in CLAUDE.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Condense CLAUDE.md by removing detailed build, test, architecture, release, and pre-commit sections; add a concise 'How to run' example and a brief 'Configuration' heading to surface primary CLI usage and simplify the documentation.
Delete legacy .agents skill docs (get-api-docs, python-code-review) and add configuration and docs for Claude integration. Adds .claude/settings.json to enable WebSearch/WebFetch, register plugins, and run pre/post tool hooks (ruff/pyright auto-checks and auto-fixes). Adds CLAUDE.md with project overview, build/test instructions, architecture, and conventions.
- cli: log metadata strip failures to verbose instead of swallowing
- cli: extract _process_batch_image() from cmd_batch for readability
- cli: reuse module-level SUPPORTED_FORMATS constant in batch command
- metadata: limit C2PA binary scan to first 512KB to prevent OOM
- Remove opencv-python from [gpu] extra (conflicts with headless in base deps)
- Add graceful fallback in 'invisible' and 'all' commands when GPU deps missing
- Cache InvisibleEngine in batch mode (avoid reloading model per image)
- Fix --humanize help text (was '0.0-1.0', actual range is 0-6.0+)
- Fix stale docstring referencing non-existent [invisible] extra
- Add [gpu] extra install instructions to README
- Fix broken NeuralBleach placeholder URL in Credits
Move torch, diffusers, transformers, accelerate, controlnet-aux,
ultralytics, and safetensors into [project.optional-dependencies.gpu].
Core install now only includes lightweight deps (~20 MB vs ~1 GB):
pillow, piexif, numpy, opencv-python-headless, click, rich.
This allows web apps using fal.ai cloud GPU to skip installing
1+ GB of ML packages, reducing Docker images from 3 GB to ~300 MB
and deploy times from 14 minutes to ~3-4 minutes.
Usage:
pip install remove-ai-watermarks # core only (visible + metadata)
pip install remove-ai-watermarks[gpu] # full local GPU support
pip install remove-ai-watermarks[all] # gpu + dev tools
- Rewrite README for SEO: Nano Banana, SynthID, Made with AI, C2PA keywords
- Add Supported Models table with 7 AI services
- Add 'Made with AI' label removal to features
- Rename sections for search discoverability
- Add samples: ChatGPT/DALL-E, Midjourney, Adobe Firefly
- Reorganize data/samples with flat structure and clear naming
- Unify 'all' defaults to match 'invisible' (strength=0.02, steps=100)
- Reorder CLI docs: 'all' command first, individual commands second
- HuggingFace token is now documented as optional
- Remove 'additional setup' label from invisible section
Changes since 0.1.0:
- Fix phantom model param bug in invisible/all commands
- Fix macOS SSL certificate issue for YOLO downloads
- Use temp file in 'all' pipeline to hide intermediate output
- Add legal disclaimer and fix license attribution
- Add troubleshooting and upgrade docs to README
- Expand test suite to 137 tests covering all CLI modes
- Clean up dependencies and pyright config
- Add disclaimer section to README (research/education purposes)
- Remove incorrect Apache-2.0 license claim from ctrlregen docstrings
- Expand Credits with CtrlRegen and NeuralBleach attribution
- Add license info (MIT) for GeminiWatermarkTool and NeuralBleach
- CLI with visible, invisible, all, metadata, and batch commands
- Gemini watermark removal via reverse alpha blending
- Invisible watermark removal via diffusion regeneration (SynthID, TreeRing)
- AI metadata stripping (EXIF, PNG text, C2PA)
- Face protection (YOLO/Haar) and analog humanizer
- 137 tests covering all CLI modes and core engines
- Ruff and Pyright clean
test-user