data_preparation.py

#!/usr/bin/env python
# coding: utf-8

# In[1]:


import os
import shutil
import glob
from tqdm import tqdm


# #
# subject ID:
# xxx
# 
# image number:
# xxx
# 
# gender:
# 0 - male
# 1 - famale
# 
# glasses:
# 0 - no
# 1 - yes
# 
# eye state:
# 0 - close
# 1 - open
# 
# reflections:
# 0 - none
# 1 - low
# 2 - high
# 
# lighting conditions/image quality:
# 0 - bad
# 1 - good
# 
# sensor type:
# 01 - RealSense SR300 640x480
# 02 - IDS Imaging, 1280x1024
# 03 - Aptina Imagin 752x480
# 
# example:
# s001_00123_0_0_0_0_0_01.png

CLOSE_EYE_DIR = os.path.join("MRL Eye Data", "Prepared_Data", "Close Eyes")
OPEN_EYE_DIR = os.path.join("MRL Eye Data", "Prepared_Data", "Open Eyes")

os.makedirs(CLOSE_EYE_DIR, exist_ok = True)
print("Directory '%s' created successfully" %CLOSE_EYE_DIR)

os.makedirs(OPEN_EYE_DIR, exist_ok = True)
print("Directory '%s' created successfully" %OPEN_EYE_DIR)

                
Raw_DIR = os.path.join("MRL Eye Data", "mrlEyes_2018_01")
for dirpath, dirname, filenames in os.walk(Raw_DIR):
     for i in tqdm([f for f in filenames if f.endswith('.png')]):
         if i.split('_')[4] == '0':
                shutil.copy(src = dirpath + '/' + i, dst = CLOSE_EYE_DIR)
         elif i.split('_')[4] == '1':
                shutil.copy(src=dirpath + '/' + i, dst = OPEN_EYE_DIR)