This is a Python library designed to streamline the handling of geospatial data, particularly for machine learning applications. Working with geospatial datasets often involves challenges like rasterization, vectorization, and grid creation—this library provides efficient and easy-to-use functions to simplify these processes.

• Documentation : https://rasvec.readthedocs.io

• clip_vector_by_raster
• create_grid_on_vector
• rasterize

• patchify (divides the raster into geotagged patches)
• vectorization

• tms_to_geotiff

• view_rasters

Here's an example of a feature: Generating a grid over a vector file.

import geopandas as gpd
import matplotlib.pyplot as plt
from rasvec import create_grid_on_vector

gdf = gpd.read_file(r"sample_data/vector/vec/vec.shp")

# 
grid_cells = create_grid_on_vector("sample_data/vector/vec/vec.shp", 1000, "grid.shp")

fig, ax = plt.subplots(1,2, figsize=(10, 10))
gdf.plot(ax=ax[0])
ax[0].set_title("Original Vector Data")
gdf.plot(ax=ax[1])
grid_cells.plot(ax=ax[1], facecolor="none", edgecolor="red")
ax[1].set_title("Vector Data with Grid Overlay")
ax[0].axis("off")
ax[1].axis("off")
plt.tight_layout()

The output:

To install the library from PyPi run the below command in your terminal.

pip install rasvec

To install the development version from GitHub using Git, run the following command in your terminal.

pip install git+https://github.com/davnish/rasvec.git

This package was made possible due to the following open source projects.

• segment-geospatial
• tms2geotiff