| name | pdf-look-scanned |
| description | Make PDF documents look like they were scanned on a physical scanner. Applies realistic effects: grayscale conversion, Gaussian noise, slight rotation, blur, edge shadows, and random offset. Optionally extract real handwritten signatures from a source PDF (or user-provided images) and replace digital signatures on specific pages. Use when the user asks to: make a PDF look scanned, give a PDF a scanned appearance, replace digital signatures with real/handwritten ones, fake a scan, add scan effects to a document, or make a document look printed and scanned.
|
PDF Look Scanned
Make PDFs look like physical scans with optional signature replacement.
Dependencies
pip3 install pillow pdf2image img2pdf numpy
Also requires poppler (provides pdftoppm):
- macOS:
brew install poppler
- Ubuntu/Debian:
apt install poppler-utils
- Fedora/RHEL:
dnf install poppler-utils
- Arch:
pacman -S poppler
- Windows:
conda install -c conda-forge poppler or download from poppler releases
Quick Start
Run scripts/make_scanned.py for the core functionality. Read the script's --help for all options.
Simple scan effect
python3 scripts/make_scanned.py document.pdf
Adjust scan quality
Lower DPI and quality = grittier, more realistic cheap-scanner look:
python3 scripts/make_scanned.py document.pdf --dpi 150 --quality 75 --noise 7
Higher DPI = cleaner scan, larger file:
python3 scripts/make_scanned.py document.pdf --dpi 300 --quality 92
Signature Replacement
Finding signature coordinates
Before replacing signatures, determine crop and placement coordinates. All coordinates are fractions of page dimensions (0.0-1.0).
- Convert the source PDF to images and visually inspect to find the signature region
- Iteratively crop to isolate just the signature ink (no text, no table lines)
- On the target PDF, find the area to clear (old digital signature) and where to paste
Use this Python snippet to explore coordinates interactively:
from pdf2image import convert_from_path
from PIL import Image
pages = convert_from_path("document.pdf", dpi=200)
page = pages[0]
w, h = page.size
crop = page.crop((int(w*0.5), int(h*0.4), int(w*0.8), int(h*0.6)))
import tempfile, os
crop.save(os.path.join(tempfile.gettempdir(), "crop_test.png"))
Replace one signature
python3 scripts/make_scanned.py contract.pdf \
--sig-pdf signatures.pdf \
--sig-page 1 --sig-crop 0.41,0.33,0.62,0.42 \
--sig-target 25 --sig-clear 0.61,0.41,0.85,0.52 --sig-place 0.62,0.415
Replace multiple different signatures
Each set of --sig-page, --sig-crop, --sig-target, --sig-clear, --sig-place adds one replacement. They are matched positionally:
python3 scripts/make_scanned.py contract.pdf \
--sig-pdf signatures.pdf \
--sig-page 1 --sig-crop 0.41,0.33,0.62,0.42 \
--sig-target 25 --sig-clear 0.61,0.41,0.85,0.52 --sig-place 0.62,0.415 \
--sig-page 2 --sig-crop 0.40,0.335,0.62,0.39 \
--sig-target 27 --sig-clear 0.61,0.635,0.85,0.72 --sig-place 0.60,0.655
Signature parameters
| Parameter | Description |
|---|
--sig-pdf | Source PDF containing real signatures |
--sig-page N | Page number in source PDF (1-indexed) |
--sig-crop L,T,R,B | Crop box to extract signature (fractions) |
--sig-target N | Target page to replace signature on (1-indexed) |
--sig-clear L,T,R,B | Area to white-out old signature (fractions) |
--sig-place X,Y | Top-left position to paste new signature (fractions) |
--sig-size F | Signature width as fraction of page width (default: 0.11) |
--sig-dpi N | DPI for rendering source signature PDF (default: 350) |
Scan effect parameters
| Parameter | Default | Effect |
|---|
--dpi | 200 | Render resolution. Lower = grittier |
--quality | 85 | JPEG compression. Lower = more artifacts |
--noise | 5.0 | Gaussian noise stddev. Higher = noisier |
--blur | 0.6 | Gaussian blur radius. Higher = softer |
--rotation | 0.7 | Max rotation in degrees |
--contrast-min | 0.88 | Min contrast (lower = more washed out) |
--contrast-max | 0.95 | Max contrast |
Workflow for signature replacement
When the user provides a PDF and a separate signature source:
- Check dependencies are installed (
pillow, pdf2image, img2pdf, numpy, poppler)
- Examine the source signature PDF — convert to images, identify which pages have signatures
- Extract signatures — iteratively crop to isolate the ink, verify no text bleeds in
- Examine the target PDF — find pages with digital signatures, note the "Подпись:" or "Signature:" label positions
- Determine coordinates — clear area must cover old signature without eating into labels; place position should be right after the label
- Run the script with all parameters
- Verify output — check signature pages visually, adjust coordinates if needed
- Check metadata — run
exiftool on the output to ensure no software traces remain
Common pitfalls:
- Crop box too tight: signature strokes get clipped on edges
- Clear area too wide: eats into "Подпись:"/"Signature:" labels or surrounding text
- Signature too large/small: adjust
--sig-size (0.11 is typical for contracts)
- Source PDF is a phone photo: use higher
--sig-dpi (350+) and higher ink threshold
