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Roboflow | OneFormer - SOTA Instance Segmentation with Detectron2 | Tutorial | Google Colab @Roboflow | Uploaded 1 year ago | Updated 3 hours ago
OneFormer is fresh segmentation model that earned 5x state-of-the-art badges from Papers with Code. Model managed to beat MaskFormer and Mask2Former and is now ranked number one in Instance, Semantic and Panoptic Segmentation. Take a look at our Google Colab tutorial and learn how to use it in your Computer Vision project.

Chapters:
0:00 Introduction
0:45 Semantic vs Instance vs Panoptic
1:38 Inference Demo
2:50 Setting up python environment
4:02 ADE20K Dataset
5:36 Cityscapes Dataset
6:23 COCO Dataset
7:15 Roboflow Notebooks
8:04 Measure size of the real life object using segmentation
16:55 Outro

Roboflow: roboflow.com
Roboflow Universe: universe.roboflow.com
Roboflow Notebooks: github.com/roboflow-ai/notebooks
OneFormer GitHub repository: github.com/SHI-Labs/OneFormer
OneFormer arXiv paper: arxiv.org/abs/2211.06220
"How to Train Detectron2 on Custom Object Detection Data" Blog Post: blog.roboflow.com/how-to-train-detectron2
"Measure Distance in Photos and Videos Using Computer Vision" Blog Post: blog.roboflow.com/computer-vision-measure-distance

Stay up to date with the projects I'm working on at github.com/roboflow-ai and github.com/SkalskiP!
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OneFormer - SOTA Instance Segmentation with Detectron2 | Tutorial | Google Colab @Roboflow

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