FGIDetect

Face and Gesture Image Detection
FGIDetect is a project to detect face and guesture using camera capture technology.

Requirements

Python 3.6.1 OpenCV 3.4.1 Keras 2.0.2 Tensorflow 1.2.1 Theano 0.9.0
Windows or Linux (macOS not officially supported, but might work)
Suggestion: Better to download Anaconda as it will take care of most of the other packages and easier to setup a virtual workspace to work with multiple versions of key packages like python, opencv etc.
Repo contents
ui_setup.py: The main script launcher. This file contains all the code for UI options and OpenCV code to capture camera contents. This script internally calls interfaces to gesture_recognize.py and camera_face.py.
gesture_recognize.py: This script file holds all the CNN specific code to create CNN model, load the weight file (if model is pretrained), train the model using image samples present in ./train_set2, visualize the feature maps at different layers of NN (of pretrained model) for a given input image present in ./train_set2 folder.
camera_face.py: This script file holds the face recognition code to recognize face through camera video, load the user name using face image samples present in ./dataset folder.
Installation Options:
install this module from pypi using pip3 (or pip2 for Python 2):
```
pip3 install face_recognition
```
Usage
On Windows
```
python ui_setup.py
```
features
This application comes with CNN model to recognize upto 4 pretrained gestures:
OK
One
Two
Five

This application provides following functionalities:

Prediction : Which allows the app to guess the user’s gesture against pretrained gestures. App can dump the prediction data to the console terminal or to a json file directly which can be used to plot real time prediction bar chart (you can use my other script
New Training : Which allows the user to retrain the NN model. User can change the model architecture or add/remove new gestures. This app has inbuilt options to allow the user to create new image samples of user defined gestures if required.
Visualization : Which allows the user to see feature maps of different NN layers for a given input gesture image. Interesting to see how NN works and learns things.