Segment Anything Model for Geospatial Data¶

This notebook shows how to use segment satellite imagery using the Segment Anything Model (SAM) with a few lines of code.

Make sure you use GPU runtime for this notebook. For Google Colab, go to Runtime -> Change runtime type and select GPU as the hardware accelerator.

Install dependencies¶

Uncomment and run the following cell to install the required dependencies.

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# %pip install leafmap

# %pip install leafmap

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# %pip install segment-geospatial localtileserver

# %pip install segment-geospatial localtileserver

Import libraries¶

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import os
import leafmap
import torch
from samgeo import SamGeo, tms_to_geotiff

import os import leafmap import torch from samgeo import SamGeo, tms_to_geotiff

Create an interactive map¶

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m = leafmap.Map(center=[29.676840, -95.369222], zoom=19)
m.add_basemap('SATELLITE')
m

m = leafmap.Map(center=[29.676840, -95.369222], zoom=19) m.add_basemap('SATELLITE') m

Pan and zoom the map to select the area of interest. Use the draw tools to draw a polygon or rectangle on the map

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if m.user_roi_bounds() is not None:
    bbox = m.user_roi_bounds()
else:
    bbox = [-95.3704, 29.6762, -95.368, 29.6775]

if m.user_roi_bounds() is not None: bbox = m.user_roi_bounds() else: bbox = [-95.3704, 29.6762, -95.368, 29.6775]

Download map tiles¶

Download maps tiles and mosaic them into a single GeoTIFF file

In [ ]:

image = 'satellite.tif'
tms_to_geotiff(output=image, bbox=bbox, zoom=20, source='Satellite')

image = 'satellite.tif' tms_to_geotiff(output=image, bbox=bbox, zoom=20, source='Satellite')

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# image = '/path/to/your/own/image.tif'

# image = '/path/to/your/own/image.tif'

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m.add_raster(image, layer_name='Image')
m

m.add_raster(image, layer_name='Image') m

Initialize SAM class¶

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out_dir = os.path.join(os.path.expanduser('~'), 'Downloads')
checkpoint = os.path.join(out_dir, 'sam_vit_h_4b8939.pth')

out_dir = os.path.join(os.path.expanduser('~'), 'Downloads') checkpoint = os.path.join(out_dir, 'sam_vit_h_4b8939.pth')

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device = 'cuda' if torch.cuda.is_available() else 'cpu'
sam = SamGeo(
    checkpoint=checkpoint,
    model_type='vit_h',
    device=device,
    erosion_kernel=(3, 3),
    mask_multiplier=255,
    sam_kwargs=None,
)

device = 'cuda' if torch.cuda.is_available() else 'cpu' sam = SamGeo( checkpoint=checkpoint, model_type='vit_h', device=device, erosion_kernel=(3, 3), mask_multiplier=255, sam_kwargs=None, )

Segment the image¶

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mask = 'segment.tiff'
sam.generate(image, mask)

mask = 'segment.tiff' sam.generate(image, mask)

Polygonize the raster data¶

Save the segmentation results as a GeoPackage file.

In [ ]:

vector = 'segment.gpkg'
sam.tiff_to_gpkg(mask, vector, simplify_tolerance=None)

vector = 'segment.gpkg' sam.tiff_to_gpkg(mask, vector, simplify_tolerance=None)

You can also save the segmentation results as any vector data format supported by GeoPandas.

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shapefile = 'segment.shp'
sam.tiff_to_vector(mask, shapefile)

shapefile = 'segment.shp' sam.tiff_to_vector(mask, shapefile)

Visualize the results¶

In [ ]:

style = {
    'color': '#3388ff',
    'weight': 2,
    'fillColor': '#7c4185',
    'fillOpacity': 0.5,
}
m.add_vector(vector, layer_name='Vector', style=style)
m

style = { 'color': '#3388ff', 'weight': 2, 'fillColor': '#7c4185', 'fillOpacity': 0.5, } m.add_vector(vector, layer_name='Vector', style=style) m

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Last update: 2023-04-22
Created: 2023-04-22