This is a repo created for the first assignment.
1.The train.py code has the model as instructed with 3 convolution layers and 2 fully connected layers.
2.predict.py takes image all the images from the directory as input and gives binary output for all of them.
3.plot.py shows the accuracy of the model with number of epochs.
This code takes image of an eye as input and gives the detected contour of pupil as output.
To compile the code use the command:-
g++ pupil_detection.cpp pkg-config --cflags --libs opencv -o pupil_detection
To run the file, use the command:-
./pupil_detection
This code takes synthetic image of pupil as an input and gives out the projection of sphere and 3-D circle on a new image and also the center, radius and normal of the 3-D circle(on the terminal).
To run the code use the command:-
g++ pupil_pose_estimation.cpp pkg-config --cflags --libs opencv -o pupil_pose_estimation
To run the file, use the command:-
./pupil_pose_extimation
