Simple Crack Detection using Machine Vision technique.
This respository consists of the code for Semantic segmantation using several Deep Learning Architectures.
- Reduced Space and Memory complexity while comparing to Deep Learning based architectures.
- The training module has been built using Pycharm 2018.1.4.
- The System requirement’s are 2.7 GHz Intel Core i5 with atleast 4 GB of RAM.
You can use Anaconda to install opencv with the following command line.:
conda install -c conda-forge opencv
You can use Anaconda to install opencv with the following command line.:
conda install -c conda-forge opencv
You can use PIP to install the module numpy with the following command line.:
pip install numpy
Run the following script to dispatch the predictor.
python3 app.py
Don't feel shy to drop a star, if you find this repo useful. I would love for you to contribute to Detect-Cracks, check the LICENSE file for more info.
Stanly Moses – @Linkedin – stanlimoses@gmail.com
Distributed under the MIT license. See LICENSE for more information.