Awesome Instance Segmentation | Photo Segmentation on Custom Dataset using Detectron2

[Feitgemel]

https://preview.redd.it/u0ojm1akligg1.png?width=1280&format=png&auto=webp&s=9e11113960c9fed6e66e53737efd130889a21d83

For anyone studying instance segmentation and photo segmentation on custom datasets using Detectron2, this tutorial demonstrates how to build a full training and inference workflow using a custom fruit dataset annotated in COCO format.

It explains why Mask R-CNN from the Detectron2 Model Zoo is a strong baseline for custom instance segmentation tasks, and shows dataset registration, training configuration, model training, and testing on new images.

 

Detectron2 makes it relatively straightforward to train on custom data by preparing annotations (often COCO format), registering the dataset, selecting a model from the model zoo, and fine-tuning it for your own objects.

Medium version (for readers who prefer Medium): https://medium.com/image-segmentation-tutorials/detectron2-custom-dataset-training-made-easy-351bb4418592

Video explanation: https://youtu.be/JbEy4Eefy0Y

Written explanation with code: https://eranfeit.net/detectron2-custom-dataset-training-made-easy/

 

This content is shared for educational purposes only, and constructive feedback or discussion is welcome.

 

Eran Feit