Panoptic Segmentation using Detectron2
Eran Feit
Panoptic segmentation is a challenging task in computer vision that combines instance segmentation and semantic segmentation. Detectron2, a state-of-the-art deep learning library for object detection and segmentation, provides powerful tools for panoptic segmentation. With Detectron2, researchers and developers can leverage the latest advancements in deep learning to tackle real-time panoptic segmentation in Python. By integrating instance and semantic segmentation, panoptic segmentation aims to achieve accurate and comprehensive understanding of visual scenes, enabling advanced applications in areas like autonomous driving, robotics, and image analysis. Detectron2 offers an awesome panoptic segmentation model, widely regarded as one of the best panoptic segmentation models available, making it an invaluable resource for image segmentation projects involving AI and deep learning techniques for panoptic photo segmentation.
In this tutorial we will learn how to run live and real time image inference of Panoptic segmentation using Detectron2.
We will learn to install it on Windows and Linux , and code the inference Python code and get the results in seconds .
You can download the code here : https://ko-fi.com/s/7317da4e07
You can find more cool Instance segmentation projects and tutorials in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4Y24C9LW1AjffKmgGUyaInz
A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V
I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ".
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