Computer Vision Models

Description:

All models (optimized,pre-built and trained) for my work are listed here

Pre-Built

• detect_gender - CLI for gender detection on static 2-D image
• gender_detection_model - Pre-Built Model
• gender_detect_webccam - CLI for gender detection on video frames
• smallervggnet - Small VGG Net Model Architecture
• train - Builder Script
• Age_Gender_Pre_Built - Based on VGG16 Age Gender Module Built

Facial Recognition

• data_generator - Script which generates pictures using burst mode through camera
• Training - Training for similarity using LBPH Recognizer
• main - Main App which gives similarity metric

Trained

Built on easily availaible datasets and images generated from OpenVINO Toolkit Models

• build_imfdb - Build Database Script
• opt_model.h5 - Optimized Model
• SMALL_VGG_NET - Initial Model Build
• smallvggnet - optimized Model Build
• train_model - Training Scipt for Model with multiple outputs
• init - Model,Graph Initializer
• convertor - .svg to .png convertor
• deploy.prototxt - caffemodel specs
• gen - qrcode generator
• integrator - Model(s) integrator
• new_face_detection - Script for GUI Build and interface
• res10_300x300_ssd - CaffeModel
• new_model - Model with OpenVINO Trainers
• xception - Xception Net with IMFDB Trainers
• Age_Gender_Continous - Age Gender Module (Densenet121) with Continous Age
• Age_Gender_Categorical - Age Gender Module (Densenet121) with Softmax Ages
• Age_Gender_One_Hot - Age Gender Module (Densenet121) with One Hot Ages

Human Detector

Built on imageai library with RetinaNet,YoloV3

• hum_detector - Human Detector on pictures
• hum_detector_pic_resnet50 - Same as above but with Model Loader Changed
• hum_detector_self - Detector on vid frames