This project an basic application of ontent base image retrival system and relative feedback system. To use code you should download conda environment and use conda for dowloading external libraries.
Program contains ;
A gui (used with PyQT framework)
A classifier (SVM classifer used. The train and test code is inspired from this github user.
A google image/url search service (URL for geting result of svm classifier from web. Images for relative feedback on second gui)
A Second gui for relative feedback system (Used with PyQt framework)
The usage of program details explained on Wiki page of this repository The program Basicly has two Gui
The first gui has 4 button which are
Open Image : is using for selecting images which will predicted from pre-trained svm classifier and searched from google web services
Open Retrived Images : opens Second gui for dowloaded images froom google image service in order to update train set efficiently
Train Data Set: re-trains and saves the svm classifer.
Close : Terminates program.

The second gui has 2 button and images for relative feedback ;
Relative feed back images : is also button which contains images. When user select an image program takes the path of image . The selected make those buttond dissapear for avoding multiple selection.
Update : moves selected images from temp folder to selected file location. After moving object renames all directory according to ascending order. Thanks to that after update users can re-train data sets.
Cancel: Disposes the second gui.