mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-10-14 21:40:47 +02:00
Victor Kuznetsov
16bc9879e9
Extract TwoStageZImagePipeline shared base from QwenZImagePipeline so all three profiles are siblings, not a chain. Add ChromaZImagePipeline on that base with diffusers ChromaImg2ImgPipeline bf16, neutral calibrated prompt, guidance 5.0, four effective steps with Diffusers truncation compensation, no Canny. Flat vendor floors from the 2026-08-29/30 oracle calibration across OpenAI (0.09), Microsoft InvisMark (0.125), Google (0.40), Meta Content Seal (0.17), seed-stability verified on Meta, full-path face-stage interaction clean through the Gemini oracle. Research record in docs/chroma1-engine-research.md with the matched-strength addendum showing Chroma1 regenerates better per unit strength but its boundaries scatter wider than qwen's. Fix text-manifest guard to reject chroma-zimage at the boundary, update all profile references from 'both' to 'all three' across src, docs, README, and python-api.
Maintainer scripts
These scripts are development and evaluation tools, not installed CLI commands. Run
them from the repository root with uv run python scripts/<name>.py --help. Inputs
under .local-eval/ and generated reports remain untracked unless a data README
explicitly names a tracked canonical result.
Audits and release checks
| Script | Purpose |
|---|---|
corpus_gap_scan.py |
Compare a local image corpus with the library's identify results. |
detection_timing.py |
Record per-method metadata and verdict timings. |
detection_timing_report.py |
Aggregate timing records by method and segment. |
fidelity_metrics.py |
Compute objective image-fidelity metrics for paired outputs. |
invisible_quality_audit.py |
Pair originals and invisible-removal outputs for quality review. |
metadata_removal_audit.py |
Check metadata detection/removal parity over a corpus. |
pill_gate_audit.py |
Measure the Jimeng pill detector on the product path. |
real_examples_e2e.py |
Run end-to-end confidence checks over local examples. |
record_parity_audit.py |
Compare record-based and file-based identification. |
resource_ceilings.py |
Measure peak RSS and runtime for fill backends. |
robustness_suite.py |
Exercise CLI failures on adversarial and degenerate inputs. |
sidecar_regression.py |
Compare current identification with recorded sidecars. |
smoke_matrix.py |
Exercise CLI parameter choices on real local data. |
video_fidelity_probe.py |
Compare delivered video fidelity with its source. |
visible_eval.py |
Benchmark registered visible-mark detectors. |
visible_removal_audit.py |
Audit visible-removal results over a local corpus. |
Calibration and corpus preparation
| Script | Purpose |
|---|---|
contentseal_transforms.py |
Reproduce and hash-check deterministic Content Seal variants. |
detector_response.py |
Measure detector response over mark size, contrast, background, and aspect. |
fill_quality.py |
Measure visible-fill quality against constructed ground truth. |
ladder_headroom.py |
Measure recall cost from the coarse scale ladder. |
registered_mark_calibrate.py |
Measure a registered detector without conflating visual positives, metadata cohorts, adjudicated negatives, and unlabeled controls. |
synthid_corpus.py |
Ingest and inspect the local SynthID reference corpus. |
vendor_cohort_harvest.py |
Partition TC260 carriers by producer code. |
vendor_mark_calibrate.py |
Calibrate a candidate vendor text detector. |
visible_alpha_solve.py |
Rebuild visible-watermark alpha assets from controlled captures. |
visible_groundtruth.py |
Consolidate blinded contact-sheet labels into ground truth. |
visible_positives.py |
List corpus images carrying a registered visible mark. |
visible_recall_sample.py |
Build an unbiased blinded sample for recall measurement. |
visible_sheets.py |
Build blinded contact sheets for relaxation candidates. |
Research and diagnostic prototypes
| Script | Purpose |
|---|---|
cjk_tail_probe.py |
Test a generic template for otherwise uncovered CJK labels. |
controlnet_sweep.py |
Sweep the historical ControlNet removal prototype. |
infer_text_lines.py |
Draft stable source-text lines without modifying pixels. |
qwen_scrub_prototype.py |
Probe low-strength Qwen regeneration on a GPU. |
selective_text_restoration.py |
Evaluate text restoration over a scrubbed image. |
synthid_pixel_probe.py |
Run the experimental local SynthID carrier probe. |
video_synthid_sweep.py |
Build oracle-gated video regeneration candidates. |
Generated assets
| Script | Purpose |
|---|---|
render_pill_silhouette.py |
Render the synthetic Jimeng pill silhouette. |
render_vendor_silhouettes.py |
Render synthetic vendor text-mark silhouettes. |
Shared helpers
_plain_console.py provides plain-text fallbacks for Rich output, and
_text_eval.py contains normalization helpers shared by text-evaluation scripts.