Please note that even though there are separate files for each task (a1, a2, b1, b2), the main file is main_jupyter.ipynb, and only this file contains the extensive data and model exploration.
Running "tree --filelimit 20" from the location of this README.md, we get the following structure.
.
├── AMLS_19-20_SN16076397
│ ├── A1
│ │ └── a1.py -> Contains the code which created CNN, trains, test.
│ ├── A2
│ │ └── a2.py -> Contains the code which created CNN, trains, test.
│ ├── B1
│ │ └── b1.py -> Contains the code which created CNN, trains, test.
│ ├── B2
│ │ └── b2.py -> Contains the code which created CNN, trains, test.
│ ├── Datasets
│ │ ├── cartoon_set
│ │ │ ├── img [10000 entries exceeds filelimit, not opening dir]
│ │ │ └── labels.csv
│ │ ├── cartoon_set_test
│ │ │ ├── img [2500 entries exceeds filelimit, not opening dir]
│ │ │ └── labels.csv
│ │ ├── celeba
│ │ │ ├── img [5000 entries exceeds filelimit, not opening dir]
│ │ │ └── labels.csv
│ │ └── celeba_test
│ │ ├── img [1000 entries exceeds filelimit, not opening dir]
│ │ └── labels.csv
│ ├── README.md -> The file you're reading now.
│ ├── common.py -> Contains functions used across a1.py, a2.py, b1,py, b2.py.
│ ├── main.py -> Runs a1.py, a2.py, b1,py, b2.py, prints results.
│ ├── main_jupyter.ipynb -> The main file in which extensive data and model exploration are made.
│ └── shape_predictor_68_face_landmarks.dat -> Used by dlib.
└── README.md -> The file you're reading now.
17 directories, 19 files
cv2
dlib
matplotlib
numpy
os
random
sklearn
tensorflow