GIS / OCR Engineer: Raster Map Text Extraction from WMS
2 days ago
Job description
We are building a geospatial data extraction pipeline for planning and cadastral map raster layers served via WMS.The core challenge is to extract, georeference, and classify map annotations (mainly text and numbers, possibly lines) from raster map tiles in a way that is reliable, scalable, and reproducible over large geographic areas.
The basic workflow will include:
- Text extraction and recognition for a raster (WMS) layer using e.g. OCR
- Automated QA, classifying and georeferencing text objects
- Assigning each text object into polygons
- Large municipality-level datasets; varying from km2 with tens of thousands of text blocks)
- 1-10 datasets depending on success and accuracy for output results
- GIS fundamentals (raster to vector, georeferencing, tiling)
- Medium to strong Python engineering skills
- Experience with raster processing and GDAL ecosystem tools
- OCR or computer vision experience applied to non-document imagery
- Ability to reason about map symbology, labels, and visual artifacts
- Great communication skills (English)
- Experience with WMS / GeoServer-based workflows
- PaddleOCR, MMOCR, or similar OCR frameworks
- Large-scale geospatial batch processing
- QGIS scripting or plugin experience
- Prior work with digitizing/vectorizing cartographic or planning maps
The end goal is to extract text objects with a very high accuracy and label polygons based on these text objects.
Keywords
- OCR, text extraction, text recognition, GIS, mapping, map digitizing, raster analysis
Mandatory skills:
Python, Machine Learning, Natural Language Processing, Deep Learning, OCR Algorithm, OCR Software, Text Recognition
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