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Unet With Transform
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Unet With Transform

Developed by qubvel-hf
A PyTorch implementation of the Unet image segmentation model, supporting various encoder architectures and pretrained weights.
Image Segmentation
Safetensors
Open Source License:MIT#Image Segmentation#ResNet Encoder#Medical Imaging
Downloads 22
Release Time : 8/23/2024

Model Overview

This model is an implementation of the Unet architecture for semantic segmentation tasks, suitable for various scenarios such as medical imaging and satellite imagery segmentation.

Model Features

Multiple Encoder Support
Supports mainstream encoder architectures like ResNet, allowing flexible selection of backbone networks.
Pretrained Weights
Supports initialization with ImageNet pretrained weights to enhance model performance.
Modular Design
The decoder supports modules like batch normalization and attention mechanisms, enabling flexible configuration as needed.

Model Capabilities

Image Segmentation
Semantic Segmentation
Medical Image Analysis
Satellite Image Processing

Use Cases

Medical Imaging
Organ Segmentation
Used for organ identification and segmentation in CT or MRI images
Remote Sensing
Land Cover Classification
Used for identifying and classifying surface features in satellite images
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