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DeepForest itself is pure Python and will work on all major operating systems, but has spatial and deep learning dependencies that can be harder to install, particularly on Windows. To make this easier DeepForest can also be installed using conda and mamba.
1 Φεβ 2021 · An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)
DeepForest is a python package for training and predicting ecological objects in airborne imagery. DeepForest currently comes with a tree crown object detection model and a bird detection model. Both are single class modules that can be extended to species classification based on new data.
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. DeepForest models can also be extended to species classification based on new data. DeepForest is designed for:
The stable version is available via using: $ pip install deep-forest. The package is portable and with very few package dependencies. It is recommended to use the package environment from since it already installs all required packages.
1 Φεβ 2021 · DF21 is an implementation of Deep Forest 2021.2.1. It is designed to have the following advantages: Powerful: Better accuracy than existing tree-based ensemble methods. Easy to Use: Less efforts on tunning parameters. Efficient: Fast training speed and high efficiency. Scalable: Capable of handling large-scale data.
How to Get Started ¶. This is a quick start guide for you to try out deep forest. The full script is available at Example. Installation ¶. The package is available via PyPI. As a kind reminder, do not forget the hyphen (-) between deep and forest. $ pip install deep-forest. Load Data ¶.
