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Segformer Test V5
S
Segformer Test V5
Developed by nielsr
A visual model for semantic segmentation of sidewalk scenes, capable of identifying and segmenting different objects and areas on sidewalks.
Downloads 14
Release Time : 4/8/2022
Model Overview
This model specializes in semantic segmentation tasks for sidewalk scenes, accurately identifying and segmenting elements such as sidewalks, roads, and obstacles, suitable for urban planning and autonomous driving applications.
Model Features
High-Precision Segmentation
Capable of accurately segmenting different objects and areas in sidewalk scenes.
Versatile Application
Suitable for various outdoor scenes such as urban streets and sidewalks.
Model Capabilities
Image Segmentation
Semantic Recognition
Use Cases
Urban Planning
Sidewalk Analysis
Used to analyze the layout and obstacle distribution of urban sidewalks.
Provides detailed sidewalk segmentation results to help optimize urban design.
Autonomous Driving
Pedestrian Path Recognition
Assists autonomous vehicles in identifying pedestrian pathways.
Enhances the perception capabilities of autonomous systems in sidewalk areas.
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