mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-08-09 23:50:40 +02:00
Victor KuznetsovandClaude Opus 5
bf4bfc1ab7
The min-resolution floor lifted small inputs toward SDXL's ~1024 training size, and Real-ESRGAN was an optional way to do that lifting. Both surviving profiles run at native geometry, so the engine forced the floor to 0 on every path; the floor never fired, `upscaling` was never true, and nothing downstream of it could execute. Gone: upscaler.py, _esrgan_upscale, the min_resolution and upscaler parameters, _target_size's floor branch, --min-resolution, --upscaler, _warn_if_esrgan_unavailable and the `esrgan` extra. max_resolution stays and is now the only lever on geometry; it can only scale down. scripts/smoke_matrix.py was the one live consumer and neither gate saw it - Pyright is scoped to src/ and Ruff cannot resolve its function-local import - so `--diffusion` would have died at import. Its knob rows were written for the removed profiles besides (--pipeline sdxl, --steps 20, --guidance-scale 5.0, --device mps), so they are rewritten rather than patched: most now assert a knob is REJECTED, which is the coverage worth having when the CLI accepts a value the library refuses several layers down. Accepted-knob rows skip without CUDA, so the row count is host-dependent and verification-plan.md no longer claims a fixed 68. This removes a public module, a CLI option and a published extra, so the next release is 0.25.0, not a patch. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
219 lines
6.1 KiB
Markdown
219 lines
6.1 KiB
Markdown
# Installation
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Python 3.10.1 or newer is required.
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## Default metadata mode
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The default package provides:
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- provenance inspection;
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- AI metadata inspection and removal.
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It installs Pillow, piexif, and c2pa-python for reading metadata directly from
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files. It does not install NumPy, OpenCV, pillow-heif, Torch, diffusion models,
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or invisible-watermark decoders.
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Install it as an isolated command with uv:
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```bash
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uv tool install remove-ai-watermarks
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```
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Or with pipx:
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```bash
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pipx install remove-ai-watermarks
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```
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You can also install the Homebrew package on macOS or Linux:
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```bash
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brew install wiltodelta/tap/remove-ai-watermarks
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```
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## Visible watermark removal
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Visible mark detection, OpenCV inpainting, and manual region erasing need the
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`visible` extra:
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```bash
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uv tool install --force "remove-ai-watermarks[visible]"
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```
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Add `heif` only when the pixel path must decode HEIC, HEIF, or AVIF:
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```bash
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uv tool install --force "remove-ai-watermarks[visible,heif]"
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```
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## Video processing
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Video metadata inspection and stripping work with the default package. Stable
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visible-mark identification and removal, full video cleaning, and visible/all
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batch modes need the `video` extra:
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```bash
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uv tool install --force "remove-ai-watermarks[video]"
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```
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The extra includes the visible pixel runtime and PyAV for preserving variable
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frame timestamps. Video SynthID regeneration also needs the diffusion stack:
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```bash
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uv tool install --force "remove-ai-watermarks[video,diffusion]"
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```
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## Invisible watermark removal
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Diffusion based removal needs the `diffusion` extra:
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```bash
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uv tool install --force "remove-ai-watermarks[diffusion]"
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```
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The code supports CUDA, XPU, MPS, and CPU devices. A GPU is recommended because
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CPU inference is slow.
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For the CUDA only Qwen Image plus Z-Image profile:
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```bash
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uv tool install --force "remove-ai-watermarks[qwen-zimage]"
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```
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The `qwen-zimage` extra includes the normal `diffusion` dependencies.
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## Feature extras
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Extras are composable. Install only the capabilities and file formats the
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application actually uses:
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| Extra | Capability | Automatically includes | Torch or model download |
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| --- | --- | --- | --- |
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| `pixels` | Shared BGR array and image-processing runtime | NumPy, headless OpenCV | No |
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| `heif` | HEIC, HEIF, and AVIF pixel decoding | pillow-heif | No |
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| `visible` | Visible mark detection, OpenCV inpainting, and manual erasing | `pixels` | No |
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| `video` | Visible video identification/removal and timestamp preservation | `visible`, PyAV | No |
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| `detect` | Open DWT-DCT detection for Stable Diffusion, SDXL, and FLUX | `pixels`, PyWavelets | No |
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| `trustmark` | Adobe TrustMark detection | trustmark | Yes |
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| `diffusion` | Diffusion-based invisible watermark removal | `pixels`, Torch, Diffusers | Yes |
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| `migan` | MI-GAN ONNX fill backend | `visible`, ONNX Runtime | Model download, no Torch |
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| `lama` | big-LaMa ONNX fill backend | `visible`, ONNX Runtime | Model download, no Torch |
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| `qwen-zimage` | CUDA-only Qwen Image plus Z-Image pipeline | `diffusion`, DiffSynth | Yes |
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| `all` | Every production feature | All rows above | Yes |
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| `dev` | Tests, linting, typing, and upstream parity checks | `visible`, `detect`, upstream invisible-watermark | Yes, for parity tests |
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Dependency composition:
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```mermaid
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flowchart LR
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visible --> pixels
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video --> visible
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detect --> pixels
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diffusion --> pixels
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migan --> visible
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lama --> visible
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qwen["qwen-zimage"] --> diffusion
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heif
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trustmark
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```
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`heif` and `trustmark` are independent branches. Combine them explicitly with
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another feature when required. The `all` bundle contains every production
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branch but never includes `dev`.
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Examples:
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```bash
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# Metadata plus torch-free DWT-DCT detection
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uv tool install --force "remove-ai-watermarks[detect]"
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# Visible removal with HEIC/AVIF support and MI-GAN
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uv tool install --force "remove-ai-watermarks[migan,heif]"
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# Visible video removal with preserved timestamps
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uv tool install --force "remove-ai-watermarks[video]"
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# DWT-DCT and TrustMark detection without diffusion removal
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uv tool install --force "remove-ai-watermarks[detect,trustmark]"
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# Every production capability
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uv tool install --force "remove-ai-watermarks[all]"
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# An arbitrary minimal combination
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uv tool install --force "remove-ai-watermarks[migan,detect]"
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```
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`heif` stays independent so applications that only process PNG, JPEG, or WebP
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do not install libheif. `detect` uses the in-tree torch-free decoder and does
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not install the upstream `invisible-watermark` package. Optional models download
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their weights on first use.
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The old `gpu` and `remove` aliases are intentionally not provided. Use
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`diffusion` and `visible` respectively.
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## Install from the repository
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```bash
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git clone https://github.com/wiltodelta/remove-ai-watermarks.git
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cd remove-ai-watermarks
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uv sync --frozen
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```
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Add the feature groups required for your work:
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```bash
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uv sync --frozen --extra dev
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uv sync --frozen --extra dev --extra diffusion
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```
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Run commands from the repository root:
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```bash
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uv run remove-ai-watermarks --help
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```
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## Development setup
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Install development dependencies:
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```bash
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uv sync --frozen --extra dev
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```
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Run the complete project gate:
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```bash
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bash maintain.sh
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```
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The script runs dependency checks, linting, formatting checks, type checking,
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and the test suite.
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## Hugging Face authentication
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Pass a Hugging Face token directly when the selected model or account requires
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one:
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```bash
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remove-ai-watermarks invisible image.png --hf-token "$HF_TOKEN"
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```
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The CLI also loads `HF_TOKEN` from the environment and from a local `.env`
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file. The same name is documented in `.env.example`.
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## Troubleshooting
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### The first model run is slow
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Diffusion and learned fill backends may download model weights on first use.
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Later runs reuse their caches.
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### The command skips invisible removal
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The normal behavior is to skip diffusion when no supported local signal is
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found. A missing signal does not prove that the image is clean. If you know the
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image came from a relevant generator, use `--force`.
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If the CLI reports that diffusion dependencies are unavailable, install the
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`diffusion` extra. Video SynthID removal needs both `video` and `diffusion`.
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