crack-detection
There are 25 repositories under crack-detection topic.
khanhha / crack_segmentation
This repository contains code and dataset for the task crack segmentation using two architectures UNet_VGG16, UNet_Resnet and DenseNet-Tiramusu
Language:Python 330- Language:C++ 306
yhlleo / DeepSegmentor
A Pytorch implementation of DeepCrack and RoadNet projects.
Language:Python 246- Language:Python 206
shomnathsomu / crack-detection-opencv
Crack Detection On Highway Or Pavement Using OpenCV
Language:Python 109Yuki-11 / CSSR
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR) was accepted to international conference on MVA2021 (oral), and selected for the Best Practical Paper Award.
Language:Python 69anishreddy3 / Crack-Semantic-Segmentation
Real time crack segmentation using PyTorch, OpenCV and ONNX runtime
Language:Python 57xaviergoby / Deep-Learning-and-Computer-Vision-for-Structural-Crack-Detection-And-Classification
Incorporating Inductive Bias into Deep Learning: A Perspective from Automated Visual Inspection in Aircraft Maintenance
Language:Python 50choiw-public / Crack-segmentation
This repo contains customized deep learning models for segmenting cracks.
Language:Python 48dlr-wf / crackpy
Crack Analysis Tool in Python (CrackPy) - automatic detection and fracture mechanical analysis of (fatigue) cracks using digital image correlation
Language:Python 42konskyrt / Concrete-Crack-Detection-Segmentation
📅This repository contains the code for crack detection in concrete surfaces. It is a PyTorch implementation of Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
Language:Jupyter Notebook 36nhorro / tensorflow-crack-classification
CNN for crack classification, intended for use in a crack inspection pipeline (see references).
Language:Jupyter Notebook 36toxinoid00 / CrackDetection
Crack detection for concrete structure using Matlab
Language:MATLAB 26Shaggyshak / CS543_project_Image-based-Localization-of-Bridge-Defects-with-AR-Visualization
Visual inspection of bridges is customarily used to identify and evaluate faults. However, current procedures followed by human inspectors demand long inspection times to examine large and difficult to access bridges. To address these limitations, we investigate a computer vision‐based approach that employs SIFT keypoint matching on collected images of defects against a pre-existing reconstructed 3D point cloud of the bridge. We also investigate methods of reducing computation time with ML-based and conventional CV methods of segmentation to eliminate redundant keypoints. Our project successfully localizes the defect images and achieves a savings in runtime from filtering keypoints.
Language:Jupyter Notebook 20HqiTao / CT-crackseg
Official code for ICIP 2023 paper "A Convolutional-Transformer Network for Crack Segmentation with Boundary Awareness"
Language:Python 18kanishk307 / crack-detection-beproject
A python-based crack detection and classification system using deep learning; used YOLO object detection algorithm. To extract the features of cracks we used Computer Vision and developed a desktop tool using Kivy to display the outcomes.
Language:Python 16- crackeLanguage:JavaScript 11
- Language:Python 9
mo26-web / Surface-Crack-Detection-with-DL
This is a Surface Crack Detection project implemented with the Tensorflow. We fine tuning some deep learning models (like VGG 19, VGG16, MobileNetV2, ...). Use Surface Crack Detection dataset available on kaggle.
Language:Jupyter Notebook 8DZDL / DeepSegmentor
DeepCrack + Colab [DeepSegmentor] Crack and Road detection based on IA web app
Language:Jupyter Notebook 6TheSudoCoders / Granite
A pre-trained MobileNet model for detecting cracks on concrete structures
Language:Python 6biasalesc / crack-detection
Crack detection for concrete structures
Language:Python 5ruirangerfan / road_crack_detection_net
Road Crack Detection Using Deep Convolutional Neural Network and Adaptive Thresholding (IV'19)
ayush-agarwal-0502 / Concrete-Crack-Detection
Using computer vision and machine learning to detect presence of cracks in concrete structures to automate the process of damage surveillance of buildings.
Language:Jupyter Notebook 4dull-bird / highway_crack_detection
finding cracks in highway using some pattern recognition and machine learning methods.
Language:Python 4rakehsaleem / Crack-Detection-TF-1.x.x
Mask and instance-based crack detection for Python 3, Keras and TensorFlow 1.x.x
Language:Jupyter Notebook 4- Bayesian-Convolutional-Neural-Network-Crack-Detection
Tasiabueno / Bayesian-Convolutional-Neural-Network-Crack-Detection
A Bayesian Convolutional Neural Network approach for image-based crack detection and maintenance applications
Language:Jupyter Notebook 4 - Crack_Detection_transfered_learningLanguage:Jupyter Notebook 3
niemiecjakub / deep-neural-networks-in-structural-health-monitoring
Deep neural networks in structural health monitoring
Language:Jupyter Notebook 3- Language:Jupyter Notebook 1
This is my Portfolio repository
- Language:MATLAB 1
saifmanjarahmad / RoadCrackDetectionUsingCNN
Here road crack detection was done using CNN with a large dataset.
Language:Python 1starhopp3r / Granite
A pre-trained MobileNet model for detecting cracks on concrete structures.
Language:Python 1
