{"version":"1.0","type":"card","id":"23008d4f-fb97-49a8-b096-be88ea2a5759","url":"https://stacklist.com/card/23008d4f-fb97-49a8-b096-be88ea2a5759","title":"Image chips - geoai","source_url":"https://geoai.gishub.org/examples/image_chips/","note":"A Python package for processing and analyzing geospatial image data using Artificial Intelligence (AI) techniques.","image":{"url":"https://ucarecdn.com/17eb68c7-0c56-4d80-b707-0531e3ca09ef/","alt":"Image chips - geoai","width":1200,"height":630},"stack":{"id":"605a4e8e-8399-4e66-a70a-5b29f7ea1924","title":"Geospatial Data Science","url":"https://stacklist.com/stack/605a4e8e-8399-4e66-a70a-5b29f7ea1924"},"created_at":"2025-03-05T13:11:00.781Z","updated_at":null,"aco":{"summary":"This website provides an example of how to use the `geoai-py` package to generate image chips from raster and vector data. It demonstrates downloading sample data, previewing it, converting vector to raster, generating image chips, and previewing the results. The code includes detailed instructions and output for each step. \n","tags":[],"key_entities":[],"classification":null,"language":null,"confidence":null,"provenance":null,"token_counts":{"approximate":93},"content_hash":null,"acp_version":"0.2","body_available":false,"body_tokens":0,"visibility":"public","agent_accessible":true,"status":"final"},"_links":{"self":"/api/public/card/23008d4f-fb97-49a8-b096-be88ea2a5759.json","html":"https://stacklist.com/card/23008d4f-fb97-49a8-b096-be88ea2a5759","md":"/api/public/card/23008d4f-fb97-49a8-b096-be88ea2a5759.md","stack_json":"/api/public/stack/605a4e8e-8399-4e66-a70a-5b29f7ea1924.json"}}