Watermark Remover — clean-room self-learning, in-browser

Nothing here is taken from any watermark-removal product. The watermark profile is measured from your own images using a published, generic statistical idea:

• Learning. The watermark is a fixed, mostly-white overlay added the same way to every image: observed = original·(1−α) + 255·α. Across many varied images, at each watermark pixel the darkest observed values occur when the underlying picture is dark there, so the low percentile of observed luminance ≈ 255·α. Taking a low percentile per pixel across the batch (and subtracting the surrounding background level) recovers α directly; picture content, being different in every image, cancels out.
• Removal. With α known, the composite is reversed exactly: original = (observed − 255·α)/(1−α). The watermark's position in each new image is found by correlating the learned α-shape against the local brightening.

Give it enough varied images (20+) and the recovered watermark is essentially identical to the true one.