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Unet Tu Resnet18

Developed by smp-test-models
Unet image segmentation model implemented in PyTorch, supporting multiple encoder architectures
Image Segmentation
Safetensors
Open Source License:MIT#Medical Image Segmentation#Pre-trained Encoders#Multi-scale Feature Fusion
Downloads 219
Release Time : 12/23/2024

Model Overview

This is a PyTorch-implemented Unet architecture image segmentation model for semantic segmentation tasks. Supports various pre-trained encoders and is suitable for diverse image segmentation scenarios.

Model Features

Multiple Encoder Support
Supports various pre-trained encoder architectures like ResNet, facilitating transfer learning
Flexible Configuration
Configurable encoder depth, decoder channels, and other parameters to meet different needs
Pre-trained Weights
Supports initialization with ImageNet pre-trained weights

Model Capabilities

Image Segmentation
Semantic Segmentation
Medical Image Analysis
Satellite Image Analysis

Use Cases

Medical Imaging
Organ Segmentation
Segment specific organs or tissues in CT or MRI scan images
Remote Sensing
Land Cover Classification
Identify and segment different land cover types from satellite images
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