Concrete Crack Detection For Structural Audit

Getting Started

1. Clone Repo

   $ git clone https://github.com/viraja1/crack_detection.git
   

2. Change directory

   $ cd crack_detection
   

3. Install Requirements

   $ pip install -r requirements.txt
   

4. Train Model

   Skip this step if you want to use pretrained model

   Tested with python 3.7

   $ python models/model.py
   

5. Run Server

   $ python app.py
   

6. Open http://127.0.0.1:8080 in browser and use the UI to test concrete crack detection

7. Try CURL requests

   $ curl -X POST -F file=@data/train/crack/15000_1.jpg http://127.0.0.1:8080/predict
   
   {"prediction":"crack"} 
   

Screenshot

Credits

• Dataset - Concrete Crack Images for Classification (https://data.mendeley.com/datasets/5y9wdsg2zt/1/)
• Deploy Keras Model with Flask as Web App (https://github.com/mtobeiyf/keras-flask-deploy-webapp)
• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (https://www.coursera.org/learn/introduction-tensorflow)