- name
- remove-watermark
- description
- Remove light-colored text watermarks from white-background document images (exam papers, scanned documents). No API key needed - pure local image processing. Use when the user wants to remove watermarks, clean up document screenshots, or remove light text overlays from images.
Remove Watermark
Remove watermarks from white-background document images. Pure local processing, no API key needed.
When to Use
Trigger this skill when the user wants to:
- Remove watermarks from document images or screenshots
- Clean up exam paper screenshots for printing
- Remove light text overlays (e.g., "公众号·xxx", website names)
Workflow: 4-Step Process
The script path is scripts/remove_watermark.py relative to this SKILL.md. Use uv run --with Pillow --with numpy (add --with scipy only when using --region full).
Step 1: Visual Analysis (Claude reads the image)
Use the Read tool to look at a sample image. Identify:
- Is there a watermark? If no, skip processing.
- Where is it? (bottom-right corner, center, scattered across the image)
- What type? (light gray text, dark logo/stamp, colored)
- Does it overlap with content text?
Estimate the watermark region as approximate percentages: y0%, y1%, x0%, x1%.
Step 2: Brightness Analysis (script analyzes the region)
Run the analyze subcommand on the watermark region to determine the right threshold:
uv run --with Pillow --with numpy python3 <skill-path>/scripts/remove_watermark.py analyze <image> --region "y0,y1,x0,x1"Example: analyze sample.jpg --region "94,100,60,100"
This prints brightness distribution and a suggested threshold.
Step 3: Remove Watermark
Use the suggested threshold and region from Steps 1-2:
# Region mode (preferred - zero damage to text outside the region)
uv run --with Pillow --with numpy python3 <skill-path>/scripts/remove_watermark.py remove <input> -o <output> --region "y0,y1,x0,x1" --threshold <N>
# Full mode (when watermark is scattered everywhere - needs scipy)
uv run --with Pillow --with numpy --with scipy python3 <skill-path>/scripts/remove_watermark.py remove <input> -o <output> --threshold <N>Region presets: bottom-right, bottom-left, top-right, top-left, bottom, top, right, left, center, full
Custom region: --region "y0,y1,x0,x1" as percentages (e.g., "94,100,60,100" = bottom 6%, right 40%)
Step 4: Verify and Auto-Retry
Use the Read tool to check the output image. You MUST verify and retry if needed — do not stop after one attempt.
Check these two things:
- Is the watermark gone?
- Is the text content intact (not lightened or damaged)?
If watermark is still visible, retry with adjusted parameters:
| Problem | Fix |
|---|---|
| Watermark still visible | Lower the threshold (e.g., 180 → 130 → 80) |
| Only partially removed | Expand the region (e.g., widen by 5-10% in each direction) |
| Text got damaged/lightened | Raise the threshold or shrink the region to avoid text areas |
| Wrong area processed | Re-examine the image and correct the region coordinates |
Retry rules:
- Retry up to 3 times with different parameters before giving up
- Each retry: adjust ONE parameter at a time (threshold OR region, not both)
- If the suggested threshold from
analyzedidn't work, try halving it - If threshold=50 still doesn't remove the watermark, try threshold=1 with a tighter region (the region likely has no real content, so blanking it entirely is safe)
- After 3 failed attempts, report to the user what was tried and ask for guidance
Command Reference
analyze
remove_watermark.py analyze <image> [--region REGION]Prints brightness distribution and suggested threshold for a region.
remove
remove_watermark.py remove <input...> [-o OUTPUT] [--region REGION] [--threshold N] [--enhance]| Flag | Default | Description |
|---|---|---|
--region | full | Region to process (preset name or y0,y1,x0,x1) |
--threshold | 180 | Brightness cutoff for watermark pixels |
--enhance | off | Boost text contrast after removal |
--preview | off | Print stats without saving |
Tips
- Region mode is always preferred over full mode when watermark is localized. It leaves all text perfectly intact.
- For dark watermarks (logo, stamps), use a low threshold (80-120) with a tight region.
- For light gray text watermarks, use a higher threshold (160-200).
- Same batch: if all images in a folder have the same watermark position, analyze one image and apply the same settings to all.
- Combine with image-to-pdf skill: remove watermarks first, then combine into PDF.