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Segformer B0 Finetuned Segments Graffiti

Developed by Adriatogi
An image segmentation model fine-tuned on graffiti segmentation datasets based on NVIDIA's SegFormer-B0 architecture, capable of accurately identifying and segmenting graffiti areas in images.
Downloads 14
Release Time : 3/19/2024

Model Overview

This model is specifically designed for graffiti detection and segmentation, capable of separating graffiti areas from the background in images, suitable for urban management, cultural heritage preservation, and other scenarios.

Model Features

High-Precision Graffiti Segmentation
Achieves a mean Intersection over Union (IoU) of 0.8048 and an average accuracy of 0.8943 on the evaluation dataset.
Lightweight Architecture
Based on the lightweight design of SegFormer-B0, suitable for deployment in resource-constrained environments.
Dual-Category Recognition
Accurately distinguishes between graffiti areas (0.9056 accuracy) and non-graffiti areas (0.8830 accuracy).

Model Capabilities

Image Segmentation
Graffiti Detection
Pixel-Level Classification

Use Cases

Urban Management
Illegal Graffiti Monitoring
Automatically detects illegal graffiti in urban areas to assist municipal cleaning efforts.
Accurately identifies graffiti areas with an IoU of 0.7870.
Cultural Heritage Preservation
Historical Building Graffiti Restoration
Identifies graffiti areas on historical buildings to assist restoration efforts.
Achieves an accuracy of 0.8830 in identifying non-graffiti areas.
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