MjdMahasneh/Simple-PyTorch-Semantic-Segmentation-CNNs

PyTorch Implementation of Semantic Segmentation CNNs: This repository features key architectures like UNet, DeepLabv3+, SegNet, FCN, and PSPNet. It's crafted to provide a solid foundation for Semantic Segmentation tasks using PyTorch.

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This project helps developers working with image analysis by providing pre-built and configurable deep learning models for semantic segmentation. You provide images and corresponding pixel-level masks, and it trains a model to output new masks that precisely delineate objects or regions within images. It is designed for machine learning engineers and researchers who need to implement or experiment with state-of-the-art semantic segmentation techniques.

No commits in the last 6 months.

Use this if you are a developer looking for a straightforward, adaptable PyTorch implementation of popular semantic segmentation architectures to quickly train and deploy models for pixel-level image classification.

Not ideal if you are a practitioner without coding experience who needs an out-of-the-box solution to segment images, or if you require advanced capabilities beyond the core architectures provided.

image-segmentation computer-vision deep-learning-models pixel-classification machine-learning-research
No License Stale 6m No Package No Dependents
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Python

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semantic-segmentation-models

Last pushed

Nov 23, 2023

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Semantic Segmentation Models · 94 frameworks

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