geocr 1.0.1

GeOCR is a Python library for OCR, data cleaning, and historical geocoding using custom GeoJSON maps.

GeoOCR

GeoOCR is a Python library for automating OCR on historical archive images and extracting geospatial data. It provides:

• ArchiveImage: image preprocessing, splitting and OCR.
• ArchiveCollection: batch operations on collections of images.
• ArchiveGeolocator: fuzzy-match CSV addresses against a GeoJSON reference to geolocate.
• GeoExporter: export results to CSV or GeoJSON.

We recommend using it with Google Colab or Jupyter Notebook.

Note: This project was developed for a specific university research project and is not guaranteed to be maintained.

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Installation

pip install geocr

Or install from source:

git clone https://github.com/joshuavachon25/geocr-py.git
cd geocr
pip install .

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Quickstart

Normal usage involves creating a collection, batch-processing what you can, then applying specific pipelines to individual items. After that, you perform OCR, extract and correct the data, and generate a CSV file that can be used with the Geolocator along with GIS data.

from geocr.archive_image import ArchiveImage
from geocr.archive_collection import ArchiveCollection
from geocr.archive_geolocator import ArchiveGeolocator
from geocr.geo_exporter import GeoExporter
from shapely.geometry import Point
import cv2

# 1. Process an image
img = ArchiveImage(cv2.imread("/path/to/image.png"), name="example")
img.sharpen().binarize().ocr(language='fra', config='--psm 3')
print(img.ocr_text)

# 2. Batch process a folder 
col = ArchiveCollection("/path/to/images")
col.sharpen().binarize().ocr()
all_text = col.get_ocr_text()

# 3. Geocode addresses
locator = ArchiveGeolocator("rues.geojson", default_point=Point(0,0))
gdf = locator.geocode_csv(
    csv_path="adresses.csv",
    csv_fields=["No","Adresse"],
    ref_fields=["adresses"],
    similarity_threshold=85
)

# 4. Export results
GeoExporter.to_csv(gdf, "results.csv")
GeoExporter.to_geojson(gdf, "results.geojson")

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API Reference

ArchiveImage

ArchiveImage(image: np.ndarray, name: str)

Constructor: wraps an OpenCV image.

Method	Description
show(grid=False, grid_step=100, grid_color='#FF0000', subgrid_step=20, subgrid_color='#999999', title='Preview', max_size=None)	displays the image with optional grid.
save(output_dir: Path, format='png', prefix='', suffix='') -> Path	save image to disk.
split(template: str, orientation='vertical') -> list[ArchiveImage]	split image by ratios, return new ArchiveImage objects.
rotate(angle: float)	rotate image by angle in degrees.
mask(bottom=0, right=0, top=0, left=0, gray=255, color=(255,255,255))	mask borders with color.
invert()	invert image colors.
denoise(kernel=1, iterations=1) erode(kernel=1, iterations=1) dilate(kernel=1, iterations=1)	morphological operations.
binarize(mode='auto', threshold_value=127)	convert to black/white with Otsu or manual threshold.
sharpen()	apply unsharp mask.
remove_borders()	crop to largest contour.
add_borders(top=20, bottom=20, left=20, right=20, color=(255,255,255))	add uniform border.
ocr(language='fra', config='--psm 3') -> ArchiveImage	run Tesseract OCR.
get_ocr_text() -> str	display and return OCR text.
clean(rules=None, min_line_length=None)	apply regex rules and merge short lines.

ArchiveCollection

ArchiveCollection(input_path: str, is_natural_sort=True, split_template=None, split_orientation='vertical')

Constructor: loads images from folder.

Method	Description
get(name: str) -> ArchiveImage	return ArchiveImage with it's name.
remove(image_name: str)	remove image from collection.
update(original_name: str, new_images: list[ArchiveImage])	update changes from single ArchiveImage update
subset(imgs: list[str]) -> ArchiveCollection	create a new ArchiveCollection from a list of image (by name)
split_only(image_name: str, template: str, orientation='vertical')	split one image.
split_all(template: str, orientation='vertical')	split every image.
show(title='Mosaic', max_cols=6, max_size=None)	display grid of images.
copy() -> ArchiveCollection	deep copy collection.
save(output_dir: Path, format='png', prefix='', suffix='') -> list[Path]	write images to disk.
All image ops: sharpen() rotate(angle) mask(...) invert() denoise() erode() dilate() binarize() remove_borders() add_borders(...) ocr() clean()	shortcuts to apply on every image.
get_ocr_text(separator='\n', show=True)	concatenate ocr_text of all ArchiveImage and display OCR text

ArchiveGeolocator

ArchiveGeolocator(reference_geojson_path: str, default_point: Point = Point(0,0))

Constructor: loads GeoJSON reference.

gdf = geolocator.geocode_csv(
    csv_path: str = None,
    gdf: GeoDataFrame = None,
    csv_fields: list[str] = ['Adresse'],
    ref_fields: list[str] = ['nom_voie'],
    output_geometry: str = 'geometry',
    match_label: str = 'matched_ref',
    score_label: str = 'match_score',
    similarity_threshold: float = 80,
    sep: str = ';'
) -> GeoDataFrame

• If gdf provided, reuses it; otherwise loads CSV.
• Only geocodes rows where geometry is missing or equals default_point.
• Returns GeoDataFrame with original columns + output_geometry, match_label, score_label.

GeoExporter

GeoExporter.to_csv(gdf: GeoDataFrame, path: str, sep: str = ';')

Export attribute table to CSV (drops geometry).

GeoExporter.to_geojson(gdf: GeoDataFrame, path: str)

Export full GeoDataFrame to GeoJSON.

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License

This project is licensed under the MIT License. See the LICENSE file for details.