- Python 3.7
- OpenCV 3.4.6
- scikit-learn
- ./sources/Image_Augmentation_Tool/Image_Augmentation_Tool.py : Source code for generating syntetic dataset from original image
- ./sources/HOG_Classifier/HOG_Classifier.py : Source code for classify the image using HOG feature detector
- ./sources/ORB_Classifier/ORB_Classifier.py : Source code for recognize the image using ORB feature detector
- ./original_images : This is a directory that contains original image of 52 type playing card
- ./dataset/train : This is a directory that contains train images that was generated by source code Image_Augmentation_Tool.py
- ./dataset/test : This is a directory that contains test images that was generated by source code Image_Augmentation_Tool.py
cd ./sources/Image_Augmentation_Tool
python Image_Augmentation_Tool.py
cd ./sources/HOG_Classifier
python HOG_Classifier.py
cd ./sources/ORB_Classifier
python ORB_Classifier.py
Extracting feature, generating train dataset and training the classifier is taking around 10 minutes. After classifier successfully trained, program will predict all images in test dataset folder. If there is a wrong classification, program will show up the image. To continue classification process, just exit the image window. Program will result in classification result at the end.