Text Prompt Segmentation¶

This example demonstrates how to use the geoai-py package for text prompt segmentation using CLIPSeg.

Install package¶

To use the geoai-py package, ensure it is installed in your environment. Uncomment the command below if needed.

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# %pip install geoai-py

# %pip install geoai-py

Import libraries¶

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import geoai

import geoai

Download sample data¶

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raster_url = (
    "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/trees_brazil.tif"
)
raster_path = geoai.download_file(raster_url)

raster_url = ( "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/trees_brazil.tif" ) raster_path = geoai.download_file(raster_url)

Visualize data¶

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geoai.view_raster(raster_url)

geoai.view_raster(raster_url)

Initialize model¶

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segmenter = geoai.CLIPSegmentation(tile_size=512, overlap=32)

segmenter = geoai.CLIPSegmentation(tile_size=512, overlap=32)

Run inference¶

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output_path = "tree_masks.tif"
text_prompt = "trees"

output_path = "tree_masks.tif" text_prompt = "trees"

In [ ]:

segmenter.segment_image(
    raster_path,
    output_path=output_path,
    text_prompt=text_prompt,
    threshold=0.5,
    smoothing_sigma=1.0,
)

segmenter.segment_image( raster_path, output_path=output_path, text_prompt=text_prompt, threshold=0.5, smoothing_sigma=1.0, )

Visualize results¶

In [ ]:

geoai.view_raster(
    output_path,
    nodata=0,
    opacity=0.8,
    colormap="greens",
    layer_name="Trees",
    basemap=raster_url,
)

geoai.view_raster( output_path, nodata=0, opacity=0.8, colormap="greens", layer_name="Trees", basemap=raster_url, )

In [ ]:

geoai.create_split_map(
    left_layer=output_path,
    right_layer=raster_url,
    left_label="Trees",
    right_label="Satellite Image",
    left_args={"nodata": 0, "opacity": 0.8, "colormap": "greens"},
    basemap=raster_url,
)

geoai.create_split_map( left_layer=output_path, right_layer=raster_url, left_label="Trees", right_label="Satellite Image", left_args={"nodata": 0, "opacity": 0.8, "colormap": "greens"}, basemap=raster_url, )