Hello trend,
We have 2 insightful blog posts for you today on Image Segmentation.
- The Ultimate Guide to Semantic Segmentation using DeepLabv3 – With PyTorch Inference | [Notebook Link]
- Getting Started with YOLOv5 Instance Segmentation | [Notebook Link]
Semantic Segmentation vs Instance Segmentation
Semantic Segmentation classifies each pixel with a particular class. It cannot differentiate between different instances of the same class. This is where Instance Segmentation is helpful.
DeepLabv3, released in 2017, was created by a team of Google researchers to tackle the problem of semantic segmentation. Unlike its predecessor, it is an end-to-end trainable, fully Convolutional Neural Network.
DeepLabv3 cemented its status as one of the go-to models for segmentation because of its:
- ️High speed
- ️Better accuracy
- ️Architectural simplicity
- ️Generalizable to custom tasks
The YOLOv5 object detection models are well known for their excellent performance and optimized inference speed. Recently the support for instance segmentation has also been added to the codebase. With this, the YOLOv5 instance segmentation models have become some of the fastest and most accurate models for real-time instance segmentation.
Check out the blog post for learning how to use YOLOv5 Instance Segmentation in your projects.
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Satya
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