Coin Recognize Software for Computer Vision course
.
├── CMakeList.txt
├── model-final-*.h5 # Trained model of the ANN
├── model-final-*.json # Trained model of the ANN
├── src # Source files
| └── coinRecognize.cpp # Principal Class
| └── main.cpp # Main class
| └── networkTrainer.py # Trainer for the net ##RUN IT ON GOOGLE COLAB
| └── tester.py # Tester for prediction
├── include # Header file
| └── coinRecognize.h # Header for main class
├── dataset # Dataset for training divided in class
| └── 1e
| └── 2e
| └── 20c
| └── 50c
| └── unknown
├── doc # documentation folder (Doxygen)
| └── ...
└── images # Classified example images
├── pic # Sample images for testing
└── predict
└── coins # Single images of coin
└── prediction.csv # CSV file with predictions
For compiling do the following:
mkdir build
cd build
cmake ..
make
And then run with
./coinRecognize ["path_of_image"]
Use passing the path of the image that you like to test or change one of the first line of the code. If you don't pass an argument the software pick a sample images from the pic folder.
@author Denis Donadel mailto:denis.donadel@studenti.unipd.it @date 6 July 2019 @version 1.0 @since 1.0