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martibosch/
detectree-san-jose-guaviare

Name: detectree-san-jose-guaviare
Availability: InStock

gpl-3.0

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detectree weights for San José Guaviare, Colombia

Installation

This requrires detectree>=0.8.0, you can install it using pip/uv:

pip install "detectree>=0.8.0"

or conda/mamba:

conda install -c conda-forge "detectree>=0.8.0"

Example usage

Run from the command line, e.g., to predict for a single image

detectree predict-img <path-to-input-image> --output-filepath <path-to-output-image> --hf-hub-repo-id martibosch/detectree-san-jose-guaviare

or to predict for multiple images:

detectree predict-imgs <path-to-output-dir> --hf-hub-repo-id martibosch/detectree-san-jose-guaviare --img-dir <path-to-input-dir>

where <path-to-input-dir> is the path to the folder containing the .tif files. If the image files have another extension, e.g., jpeg, provide the --img-filename-pattern option as in:

detectree predict-imgs <path-to-output-dir> \
    --hf-hub-repo-id martibosch/detectree-belem \
    --img-dir <path-to-input-dir> \
    --img-filename-pattern "*.jpeg"

Additionally, you can customize the postprocessing (and many other) parameters (see the background notebook for more details) as in:

detectree predict-imgs <path-to-output-dir> \
    --hf-hub-repo-id martibosch/detectree-san-jose-guaviare \
    --img-dir <path-to-input-dir> \
    --img-filename-pattern "*.jpeg" \
    --refine-beta 10000