Albumentations on GitHub in Infrastructure
Used in 19 public GitHub repositories
Construction, transport infrastructure, structural damage, and civil inspection.

Public examples
Top public GitHub repositories
Showing the top 19
This repository contains code and dataset for the task crack segmentation using two architectures UNet_VGG16, UNet_Resnet and DenseNet-Tiramusu
444 stars137 forks[ESSD 2025 & IEEE DFC 2025 & CVPRW 2026] Bright: A globally distributed multimodal VHR dataset for all-weather disaster response
239 stars39 forksOfficial code for ICIP 2023 paper "A Convolutional-Transformer Network for Crack Segmentation with Boundary Awareness"
60 stars7 forksA Unet based modified architecture for crack detection
50 stars8 forksA Pytorch-based toolbox for three different change detection tasks, including binary change detection (BCD), semantic change detection (SCD), and building damage assessment (BDA).
36 stars2 forksThis repo collects some datasets and papers about Pavement Distress Classification. Moreover, all code will be integrated into this repo.
31 stars3 forksSelf-Supervised Multi-Scale Transformer with Attention-Guided Fusion for Efficient Crack Detection
30 stars9 forksRoad crack detection project based on NestedUnet model
22 stars3 forksThis project employs CNN and transformer models for semantic segmentation of building damage in Mexico City's 2017 earthquake, using annotated imagery to identify features like cracks and exposed rebar.
4 stars2 forksA categorical typology-based building damage classification framework using satellite imagery and deep learning
3 stars2 forksRoad damage were detected with YOLOv9
3 stars0 forksThis is Master Thesis. It is Development of a demonstrator for crack detection in sewer systems.
2 stars0 forksCode for the paper "TrueDeep: A systematic approach of crack detection with less data" (Expert Systems with Applications 2024)
1 stars0 forksMachine Learning model for detecting cracks in images of concrete
0 stars0 forks🏗️ Building damage assessment via semantic segmentation on RescueNet dataset. PyTorch implementation with focal loss for class imbalance handling.
0 stars0 forksThis project uses satellite imagery with deep learning and computer vision to detect damage caused by natural disasters like earthquakes and fires. It aims to identify damage in hard-to-reach areas, speeding up post-disaster assessments and improving resource allocation for emergency response.
0 stars0 forks이어드림 스쿨 3기 스타트업 연계 프로젝트 3팀 - 소테리아에이트 시간의 흐름에 따른 노후 인프라시설 건축물의 외관과 내부 Crack 감지
0 stars0 forks拼装币检测
0 stars0 forks- 0 stars0 forks