(getting_started)= # Getting Started ## Installation ::::{grid} 1 2 2 2 :gutter: 4 :margin: 0 5 0 0 :::{grid-item-card} Install with pip :class-card: install-card :shadow: md To install with pip from [`PyPI`](https://pypi.org/project/deepforest): ```bash pip install deepforest ``` ::: :::{grid-item-card} Install with uv :class-card: install-card :shadow: md To install with uv: ```bash uv add deepforest ``` ::: :::: ::::{grid} 1 1 1 1 :gutter: 4 :::{grid-item-card} In-depth instructions? :class-card: install-card :shadow: md Installing a specific version? Installing from source? Check the advanced installation page. +++ ```{button-ref} install :ref-type: doc :color: secondary :click-parent: true :align: center View Installation Guide ``` ::: :::: ## Intro to DeepForest DeepForest is a python package for airborne object detection and classification. ::::{grid} 1 2 2 2 :gutter: 4 :margin: 2 2 0 0 :::{grid-item} ```{image} ../../www/OSBS_sample.png :width: 100% :alt: Tree crown detection :class: shadow ``` +++ *Tree crown prediction using DeepForest* ::: :::{grid-item} ```{image} ../../www/bird_panel.jpg :width: 100% :alt: Bird detection :class: shadow ``` +++ *Bird detection using DeepForest* ::: :::: **DeepForest** is a python package for training and predicting ecological objects in airborne imagery. DeepForest comes with prebuilt models for immediate use and fine-tuning by annotating and training custom models on your own data. ```{toctree} :maxdepth: 2 :hidden: install overview intro_tutorials/index comparison ```