DPT
A PyTorch-based image segmentation model using Transformer architecture for dense prediction tasks
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Release Time : 3/22/2025
Model Overview
DPT is an image semantic segmentation model based on the Vision Transformer architecture, suitable for various dense prediction tasks. The model is provided via the segmentation_models.pytorch library, supporting multiple pretrained encoders and custom configurations.
Model Features
Transformer Architecture
Uses Vision Transformer as the encoder, suitable for image segmentation tasks
Flexible Configuration
Supports various encoder depths, feature dimensions, and output stride configurations
Pretrained Support
Can be used with pretrained weights to enhance model performance
Model Capabilities
Image Semantic Segmentation
Dense Prediction
Supports Multiple Input Resolutions
Use Cases
Computer Vision
Scene Understanding
Pixel-level semantic segmentation of complex scenes
Medical Image Analysis
Segmentation of organs or lesion areas in medical images
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