CalvinBackup/remove-ai-watermarks
1
0
Fork 0
mirror of https://github.com/wiltodelta/remove-ai-watermarks.git synced 2026-08-31 17:50:35 +02:00
Code Issues Packages Projects Releases Wiki Activity

Align watermark content with detector coverage

Browse Source
This commit is contained in:
Victor Kuznetsov
2026-08-27 20:05:03 -07:00
parent 17408b958e
commit a8d4bce14a
61 changed files with 933 additions and 198 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/visible_recall_sample.py
+4 -4
View File
@@ -1,8 +1,8 @@
"""Build an UNBIASED random sample for measuring visible-mark RECALL.
Every earlier labelling round sampled where detectors FIRED, so images that every
Every earlier labeling round sampled where detectors FIRED, so images that every
detector missed were absent by construction and recall was unmeasurable. This round
samples at random within a provenance class and shows the labeller the corners where
samples at random within a provenance class and shows the labeler the corners where
a mark can physically be, so a MISSED mark is visible as such.
Design decisions that matter:
@@ -13,11 +13,11 @@ Design decisions that matter:
recall over all uploads would mostly measure how often each vendor appears.
* NATIVE RESOLUTION crops, never a downscaled whole image: a 220px preview destroys a
faint mark (measured in an earlier round), which would inflate the miss count with
the labeller's own blindness rather than the detector's.
the labeler's own blindness rather than the detector's.
* BOTH corners per image (top-left pill, bottom-right wordmark/strip/sparkle), so one
pass adjudicates every registered mark instead of one mark per crop.
* The detector's verdict is NOT shown and is not in the sheet order -- the manifest
holds it and must not be opened until labelling ends.
holds it and must not be opened until labeling ends.
"""
from __future__ import annotations