# face_reco **Repository Path**: wanggkai/face_reco ## Basic Information - **Project Name**: face_reco - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: branch2 - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-11-26 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # face_recognition Projects are divided by several modules: **orb.py:** Uses orb descriptor on image and filters keypoints using given window (selectKP) **face_recog.py:** Using Haar Cascade, detect face. and provide window.Uses orb.py to find the keypoints in the face. **File_parser:** using directories.txt, it loads the picture and returns an array **simple_approach.py :** Using normalization, seperate,cluster,and ratio face function, it finds the distace between eyes and to the mouth region, and trains and predict with decision tree. #SAMPLE PICTURE ![alt Image(PICTURES USED FOR TESTING) ](testing.PNG) #PERFORMANCE: *HIGH SCORE == CLASS* File | ARON-SCORE | CAPRIO-SCORE |Mis-Classification| -----|-------|--------|------| aron1.jpg | 0.375 | 0.625 | TRUE| aron2.jpg | 0.660377358491 | 0.339622641509 || aron4.jpg | 0.611111111111 | 0.388888888889 || aron5.jpg | 0.40243902439 | 0.59756097561 |TRUE| aron6.jpg | 0.614035087719 | 0.385964912281 || caprio(1).jpg | 0.0698924731183 | 0.930107526882 || caprio(2).jpg | 0.25 | 0.75 || caprio(3).jpg | 0.833333333333 | 0.166666666667 |TRUE| caprio(4).jpg | 0.309523809524 | 0.690476190476 || caprio(5).jpg | 0.286885245902 | 0.713114754098 || caprio(6).jpg | 0.421686746988 | 0.578313253012 || caprio(8).jpg | 0.227272727273 | 0.772727272727 || caprio.jpg | 1.0 | 0.0 |TRUE| caprio10.jpg | 0.466666666667 | 0.533333333333 || caprio3.jpg | 0.136842105263 | 0.863157894737 || caprio4.jpg | 0.330188679245 | 0.669811320755 || caprio5.jpg | 0.774193548387 | 0.225806451613 |TRUE| caprio6.jpg | 0.13829787234 | 0.86170212766 || caprio7.jpg | 0.253623188406 | 0.746376811594 ||