Vector Features =============== Rasterio's ``features`` module provides functions to extract shapes of raster features and to create new features by "burning" shapes into rasters: ``shapes()`` and ``rasterize()``. These functions expose GDAL functions in a general way, using iterators over GeoJSON-like Python objects instead of GIS layers. Extracting shapes of raster features ------------------------------------ Consider the Python logo. .. image:: https://farm8.staticflickr.com/7018/13547682814_f2e459f7a5_o_d.png The shapes of the foreground features can be extracted like this: .. code-block:: python import pprint import rasterio from rasterio import features with rasterio.open('13547682814_f2e459f7a5_o_d.png') as src: blue = src.read(3) mask = blue != 255 shapes = features.shapes(blue, mask=mask) pprint.pprint(next(shapes)) # Output # pprint.pprint(next(shapes)) # ({'coordinates': [[(71.0, 6.0), # (71.0, 7.0), # (72.0, 7.0), # (72.0, 6.0), # (71.0, 6.0)]], # 'type': 'Polygon'}, # 253) The shapes iterator yields ``geometry, value`` pairs. The second item is the value of the raster feature corresponding to the shape and the first is its geometry. The coordinates of the geometries in this case are in pixel units with origin at the upper left of the image. If the source dataset was georeferenced, you would get similarly georeferenced geometries like this: .. code-block:: python shapes = features.shapes(blue, mask=mask, transform=src.transform) Burning shapes into a raster ---------------------------- To go the other direction, use ``rasterize()`` to burn values into the pixels intersecting with geometries. .. code-block:: python image = features.rasterize( ((g, 255) for g, v in shapes), out_shape=src.shape) By default, only pixels whose center is within the polygon or that are selected by Bresenham's line algorithm will be burned in. You can specify ``all_touched=True`` to burn in all pixels touched by the geometry. The geometries will be rasterized by the "painter's algorithm" - geometries are handled in order and later geometries will overwrite earlier values. Again, to burn in georeferenced shapes, pass an appropriate transform for the image to be created. .. code-block:: python image = features.rasterize( ((g, 255) for g, v in shapes), out_shape=src.shape, transform=src.transform) The values for the input shapes are replaced with ``255`` in a generator expression. Areas not covered by input geometries are replaced with an optional ``fill`` value, which defaults to ``0``. The resulting image, written to disk like this, .. code-block:: python with rasterio.open( '/tmp/rasterized-results.tif', 'w', driver='GTiff', dtype=rasterio.uint8, count=1, width=src.width, height=src.height) as dst: dst.write(image, indexes=1) has a black background and white foreground features. .. image:: https://farm4.staticflickr.com/3728/13547425455_79bdb5eaeb_o_d.png