**DOCUMENT SCANNER FOR PYTHON** # Phone photo in, deskewed print-ready PDF out. Deskew, orient, enhance, PDF — locally. Nothing leaves the machine: no upload, no API key, no third party holding a copy of the document you just photographed. ``` $ pip install git+https://github.com/7RPlus-GmbH/pagescan ``` ``` $ pagescan photo.jpg output.pdf INFO: Processing: photo.jpg INFO: Detection: legacy Saved: output.pdf Quality: 0.87 ``` **WHY IT EXISTS** ## Built for the documents you cannot upload. 01 ### Runs on your machine Detection, segmentation and enhancement all happen locally. The weights sit on disk; the photo never leaves the process. 02 ### Headless and scriptable One command per file, or a loop over ten thousand. No GUI, no desktop session, nothing to click — it belongs in a cron job. 03 ### Made for regulated work MIT licensed and open weight, so a compliance review can read every line and every model that touched the page. **HOW PAGESCAN READS A PAGE** ## Seven stages, two escape hatches. Stages 01–04 are model-driven and can fail. Both fallbacks rejoin the main flow, so 05–07 always run on the same contract. Input photo source **01 · LOCATE THE PAGE** 01 ### YOLO11 detector Finds the page. bbox DefaultSA24 + LCNet — on the current weights this chain beats the cascade on the held-out benchmark (44/50 vs 35/50 at IoU ≥ 0.90) and runs ~75× faster, so it is what ScanConfig() uses. The cascade is opt-in via use_cascade=True. 02 ### HQ-SAM ViT-B segmenter Refines the edge. mask 03 ### Quad fit Hull → polyDP. 4 corners 04 ### Validate & repair Quad sanity checks. valid **02 · RECTIFY** 05 ### Perspective transform Warp to a flat rectangle. flat page AltContour fallback — no usable quad, so the page is cropped to its bounding box instead. 06 ### Orientation correction Upright the page. upright **03 · FINISH** 07 ### Enhancement Shadow removal, white balance, sharpen. 300 dpi PDF output output The dashed boxes are fallbacks, not steps: a photo that detects and fits cleanly never touches them. Everything downstream of 04 receives the same shape either way, which is why a rejected quad degrades the result instead of failing the run. **OPEN WEIGHTS** ## Every model that touches the page, published. Detection, segmentation and orientation weights on Hugging Face under Apache-2.0 — audit them, fine-tune them, redistribute them. The library itself is MIT. YOLO11n Detector. Finds the page in the photo and hands on a bounding box. HQ-SAM ViT-B Segmenter. Turns the box into an edge accurate enough to fit a quad to. From SysCV’s sam-hq, Apache-2.0. MobileNetV3 small Orientation. Decides which way is up, so the rectified page comes out upright. From the OnnxTR project, Apache-2.0. FastViT-SA24 + LCNet100 The corner-regression chain that runs by default — faster than the cascade and, on the current weights, more accurate on held-out photos. From DocsaidLab’s DocAligner, Apache-2.0. **INSTALL & USE** ## One command per page. **COMMAND LINE** ``` # not on PyPI yet — install from source $ pip install git+https://github.com/7RPlus-GmbH/pagescan $ pagescan photo.jpg output.pdf # a directory of photos, one PDF each $ pagescan --batch --input-dir photos/ \ --output-dir scans/ --workers 4 # crop and perspective only, no enhancement $ pagescan photo.jpg --raw ``` **PYTHON** ``` import pagescan pagescan.scan("photo.jpg", "output.pdf") pagescan.scan_batch("input/", "output/") from pagescan import ScanConfig cfg = ScanConfig(jpeg_quality=60, deskew=True) pagescan.scan("photo.jpg", "out.pdf", config=cfg) ``` © 2026 7R+ GmbH · MIT --- Human-readable version: https://pagescan.7rplus.com/ Source: https://github.com/7RPlus-GmbH/pagescan Docs: https://7rplus-gmbh.github.io/pagescan/ Licence: MIT (library) · Apache-2.0 (model weights) Publisher: 7R+ GmbH