MobileCrackNet

Description

A crack image classifier trained on pre-trained MobileNet. The data is trained on Data Mendeley Concrete Crack Dataset. The model has an average validation accuracy of 0.9982.

Requirements

• numpy==1.19.5
• tensorflow_gpu==2.5.0

Training Guide

Refer to the Jupyter Notebook file Training.ipynb for the training guide.

Usage

Prerequisites

Make sure you have the required Python packages installed. You can install them using the following command:

pip install -r requirements.txt

Prediction

To predict the class and score for an image, run the following command:

python predict.py -m model/weights.h5 -i test/00007.jpg

Replace model/weights.h5 with the path to your trained model and test/00007.jpg with the path to the image you want to predict.

Authors

• prothej227/Journel Cabrillos