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Segformer Trainer Test
S
Segformer Trainer Test
Developed by nielsr
Image segmentation model fine-tuned on segments/sidewalk-semantic dataset based on nvidia/mit-b0 architecture
Downloads 14
Release Time : 4/19/2022
Model Overview
This model is an optimized SegFormer implementation for sidewalk semantic segmentation tasks, suitable for street scene image analysis
Model Features
Lightweight Architecture
Uses MIT-B0 as backbone network to balance performance and computational efficiency
Street Scene Optimization
Fine-tuned specifically for sidewalk semantic segmentation tasks, ideal for urban environment analysis
Model Capabilities
Image Segmentation
Semantic Scene Understanding
Street Element Recognition
Use Cases
Smart Cities
Sidewalk Condition Monitoring
Automatically identifies and analyzes sidewalk areas and obstacle distribution
Autonomous Driving
Drivable Area Identification
Assists autonomous driving systems in identifying safe passage areas
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