`Lightning Flash <https://lightning-flash.readthedocs.io/en/stable/>`_ is a high-level deep learning framework for fast prototyping, baselining, fine-tuning, and solving deep learning problems.
Flash makes complex AI recipes for over 15 tasks across 7 data domains accessible to all.
It is built for beginners with a simple API that requires very little deep learning background, and for data scientists, Kagglers, applied ML practitioners, and deep learning researchers that
want a quick way to get a deep learning baseline with advanced features PyTorch Lightning offers.
..code-block:: bash
pip install lightning-flash
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Using Lightning Flash in 3 Steps!
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1. Load your Data
-----------------
All data loading in Flash is performed via a ``from_*`` classmethod of a ``DataModule``.
Which ``DataModule`` to use and which ``from_*`` methods are available depends on the task you want to perform.
For example, for image segmentation where your data is stored in folders, you would use the ``SemanticSegmentationData``'s `from_folders <https://lightning-flash.readthedocs.io/en/latest/reference/semantic_segmentation.html#from-folders>`_ method:
..code-block:: python
from flash.image import SemanticSegmentationData
dm = SemanticSegmentationData.from_folders(
train_folder="data/CameraRGB",
train_target_folder="data/CameraSeg",
val_split=0.1,
image_size=(256, 256),
num_classes=21,
)
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2. Configure your Model
-----------------------
Our tasks come loaded with pre-trained backbones and (where applicable) heads.
You can view the available backbones to use with your task using `available_backbones <https://lightning-flash.readthedocs.io/en/latest/general/backbones.html>`_.
