Create vector labels for training deep learning models¶

Install package¶

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

In [1]:

# %pip install geoai-py

# %pip install geoai-py

Import libraries¶

In [2]:

import geoai

import geoai

Add sample datasets¶

In [3]:

m = geoai.MapLibre(style="liberty")
raster_url = (
    "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_train.tif"
)
m.add_cog_layer(raster_url, name="NAIP")
m.add_layer_control()
m.add_draw_control(
    controls=["point", "polygon", "line_string", "trash"], position="top-right"
)

m = geoai.MapLibre(style="liberty") raster_url = ( "https://huggingface.co/datasets/giswqs/geospatial/resolve/main/naip_train.tif" ) m.add_cog_layer(raster_url, name="NAIP") m.add_layer_control() m.add_draw_control( controls=["point", "polygon", "line_string", "trash"], position="top-right" )

Set default properties¶

In [4]:

properties = {
    "Type": ["Residential", "Commercial", "Industrial"],
    "Area": 3000,
    "Name": "Building",
    "City": "Seattle",
}

properties = { "Type": ["Residential", "Commercial", "Industrial"], "Area": 3000, "Name": "Building", "City": "Seattle", }

Display the interactive widget¶

In [5]:

widget = geoai.create_vector_data(m, properties, file_ext="gpkg")
widget

widget = geoai.create_vector_data(m, properties, file_ext="gpkg") widget

Out[5]: