computervision-recipes/scenarios/segmentation

Image segmentation

This directory provides examples and best practices for building image segmentation systems. Our goal is to enable the users to bring their own datasets and train a high-accuracy model easily and quickly.

Image segmentation example

Our implementation uses fastai's UNet model, where the CNN backbone (e.g. ResNet) is pre-trained on ImageNet and hence can be fine-tuned with only small amounts of annotated training examples. A good understanding of image classification concepts, while not necessary, is strongly recommended.

Notebooks

The following notebooks are provided:

Notebook name	Description
01_training_introduction.ipynb	Notebook to train and evaluate an image segmentation model.
11_exploring_hyperparameters.ipynb	Finds optimal model parameters using grid search.

Contribution guidelines

See the contribution guidelines in the root folder.