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Dpt Tu Test Vit

Developed by smp-test-models
A PyTorch-based image segmentation model library supporting various encoder-decoder architectures for semantic segmentation tasks
Image Segmentation
Safetensors
Open Source License:MIT#Dynamic Image Segmentation#ViT Encoder#Multi-scale Decoding
Downloads 228
Release Time : 4/7/2025

Model Overview

This model library provides pre-trained semantic segmentation models with encoder-decoder architecture, supporting multiple backbone networks as encoders, suitable for various image segmentation tasks.

Model Features

Multiple Encoder Support
Supports various pre-trained encoders (e.g., Vision Transformer) for flexible selection
Dynamic Image Size
Supports processing input images of different sizes
Pre-trained Weights
Provides encoder weights pre-trained on ImageNet for easy transfer learning
Modular Design
Clear encoder-decoder structure for easy customization and extension

Model Capabilities

Image Semantic Segmentation
Supports Multiple Backbone Networks
Handles Different Input Sizes
Transfer Learning Support

Use Cases

Medical Imaging
Organ Segmentation
Segment specific organs or tissues in CT or MRI images
Autonomous Driving
Road Scene Understanding
Segment key elements such as roads, vehicles, and pedestrians
Remote Sensing
Land Use Classification
Segment different land use types in satellite images
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