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udacity_preprocess_ims.py
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udacity_preprocess_ims.py
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# Copyright (c) 2017, Udacity
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
# ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
# The views and conclusions contained in the software and documentation are those
# of the authors and should not be interpreted as representing official policies,
# either expressed or implied, of the FreeBSD Project
# Author: Devin Anzelmo
import glob
import os
import shutil
import sys
import numpy as np
from scipy import misc
def make_dir_if_not_exist(path):
if not os.path.exists(path):
os.makedirs(path)
def get_mask_files(image_files):
is_cam2 = lambda x: x.find('cam2_') != -1
is_cam3 = lambda x: x.find('cam3_') != -1
is_cam4 = lambda x: x.find('cam4_') != -1
cam2 = sorted(list(filter(is_cam2, image_files)))
cam3 = sorted(list(filter(is_cam3, image_files)))
cam4 = sorted(list(filter(is_cam4, image_files)))
return cam2, cam3, cam4
def move_labels(input_folder, output_folder, fold_id):
files = glob.glob(os.path.join(input_folder, '*', '*.png'))
output_folder = os.path.join(output_folder, 'masks')
make_dir_if_not_exist(output_folder)
cam2, cam3, cam4 = get_mask_files(files)
for e,i in enumerate(cam2):
fname_parts = i.split(os.sep)
# Thanks @Nitish for these fixes:)
cam2_base = str(fold_id) + '_' + fname_parts[-3] +'_' + fname_parts[-1]
fname_parts = cam3[e].split(os.sep)
cam3_base = str(fold_id) + '_' + fname_parts[-3] +'_' + fname_parts[-1]
fname_parts = cam4[e].split(os.sep)
cam4_base = str(fold_id) + '_' + fname_parts[-3] +'_' + fname_parts[-1]
shutil.copy(i, os.path.join(output_folder,cam2_base))
shutil.copy(cam3[e], os.path.join(output_folder,cam3_base))
shutil.copy(cam4[e], os.path.join(output_folder,cam4_base))
def move_png_to_jpeg(input_folder, output_folder, fold_id):
files = glob.glob(os.path.join(input_folder, '*', '*.png'))
is_cam1 = lambda x: x.find('cam1_') != -1
cam1_files = sorted(list(filter(is_cam1, files)))
output_folder = os.path.join(output_folder, 'images')
make_dir_if_not_exist(output_folder)
for i in cam1_files:
cam1 = misc.imread(i)
fname_parts = i.split(os.sep)
cam1_base = str(fold_id) + '_' +fname_parts[-3] + '_' + fname_parts[-1].split('.')[0] + '.jpeg'
misc.imsave(os.path.join(output_folder, cam1_base), cam1, format='jpeg')
def combine_masks(processed_folder):
processed_mask_folder = os.path.join(processed_folder, 'masks')
files = glob.glob(os.path.join(processed_mask_folder, '*.png'))
cam2, cam3, cam4 = get_mask_files(files)
for e,i in enumerate(cam2):
im2 = misc.imread(i)[:,:,0]
im3 = misc.imread(cam3[e])[:,:,0]
im4 = misc.imread(cam4[e])[:,:,0]
stacked = np.stack((im4-1, im2, im3), 2)
argmin = np.argmin(stacked, axis=-1)
im = np.stack((argmin==0, argmin==1, argmin==2), 2)
base_name = os.path.basename(i)
ind = base_name.find('cam')
new_fname = base_name[:ind] + 'mask'+ base_name[ind+4:]
dir_base = str(os.sep).join(i.split(str(os.sep))[:-1])
misc.imsave(os.path.join(dir_base, new_fname), im)
os.remove(i)
os.remove(cam3[e])
os.remove(cam4[e])
def get_im_data(base_path):
folds = glob.glob(os.path.join(base_path, '*', '*'))
indicator_dict = dict()
is_val = lambda x: x.find('validation') != -1
for f in folds:
files = glob.glob(os.path.join(f, '*','*.png'))
if len(files) == 0:
indicator_dict[f] = (False, is_val(f))
else:
indicator_dict[f] = (True, is_val(f))
return indicator_dict
if __name__ == '__main__':
raw_data = os.path.join('..', 'data', 'raw_sim_data')
proc_data = os.path.join('..', 'data', 'processed_sim_data')
indicator_dict = get_im_data(raw_data)
out_val_dir = os.path.join(proc_data, 'validation')
out_train_dir = os.path.join(proc_data, 'train')
for e, i in enumerate(indicator_dict.items()):
# no data in the folder so skip it
if not i[1][0]:
continue
# validation
if i[1][1]:
move_png_to_jpeg(i[0], out_val_dir, e)
move_labels(i[0], out_val_dir, e)
# train
else:
move_png_to_jpeg(i[0], out_train_dir, e)
move_labels(i[0], out_train_dir, e)
combine_masks(out_val_dir)
combine_masks(out_train_dir)