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Segformer Test V7
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Segformer Test V7

Developed by nielsr
A vision model for semantic segmentation of sidewalk scenes, capable of identifying and segmenting different elements in images.
Image Segmentation
Transformers
Open Source License:Apache-2.0#Sidewalk Segmentation#High-Precision Semantic Segmentation#Urban Street Scene Analysis
Downloads 14
Release Time : 4/11/2022

Model Overview

This model focuses on semantic segmentation tasks in sidewalk scenes, accurately identifying and segmenting elements such as roads, pedestrians, and obstacles, suitable for urban planning and autonomous driving applications.

Model Features

High-Precision Segmentation
Accurately segments various elements in sidewalk scenes, such as roads, pedestrians, and obstacles.
Strong Scene Adaptability
Applicable to various sidewalk scenes, including urban streets and park pathways.

Model Capabilities

Image Segmentation
Scene Understanding
Semantic Annotation

Use Cases

Urban Planning
Sidewalk Facility Analysis
Used to analyze the distribution and usage of urban sidewalk facilities.
Provides detailed sidewalk facility distribution maps to assist urban planning decisions.
Autonomous Driving
Pedestrian Path Recognition
Used in autonomous driving systems to identify pedestrian paths and obstacles.
Enhances the safety and reliability of autonomous driving systems in sidewalk scenarios.
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