https://github.com/arcticray/crack-detection

A python machine learning project aimed at automatically identifying cracks on surface images using a Convolutional Neural Network.
https://github.com/arcticray/crack-detection

cnn-classification python

Last synced: 8 days ago
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A python machine learning project aimed at automatically identifying cracks on surface images using a Convolutional Neural Network.

• Host: GitHub
• URL: https://github.com/arcticray/crack-detection
• Owner: ArcticRay
• Created: 2024-11-28T21:35:45.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2024-12-06T14:49:42.000Z (28 days ago)
• Last Synced: 2024-12-09T16:51:16.083Z (25 days ago)
• Topics: cnn-classification, python
• Language: Python
• Homepage:
• Size: 396 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Surface Crack Detection

![Project Banner](outputs/sample_images.png)

## 📄 Description

**Surface Crack Detection** is a machine learning project aimed at automatically identifying cracks on surface images.

**Confusion Matrix**

![Project Banner](outputs/confusion_matrix.png)

## 🚀 Features

- **Data Preprocessing:** Loading, resizing, and normalizing images.

- **Model Training:** Development and training of a CNN for image classification.

- **Model Evaluation:** Assessing model performance with metrics and visualizations.

- **Image Classification** Uploading and classifying

## Dataset

The dataset comprises images categorized into two classes:

- **Positive:** Images containing surface cracks.

- **Negative:** Images without surface cracks.

Özgenel, Çağlar Fırat (2019), “Concrete Crack Images for Classification”, Mendeley Data, V2,

[doi: http://dx.doi.org/10.17632/5y9wdsg2zt.2x](https://data.mendeley.com/datasets/5y9wdsg2zt/2)