def run(self):
# Getting lists of images for train and test.
# Train , Test
# [ [file1, file2, ...] , [file1, file2, ...] ]
sets_with_labels = self.get_sets()
# Gets augmentations if available, empty lists otherwise.
# Train , Test
# [ [file1, file2, ...] , [file1, file2, ...] ]
augmentations = self.get_augmentations(len(sets_with_labels))
# If the augmentation reference file already exists, don't run this again.
if augmentations is None:
augmentations = [[] for _ in range(len(sets_with_labels))]
# Creates augmentation patches from the original images, it stores the information
# into pickle files.
self.augment(sets_with_labels, augmentations)
# Randomize patches for each of the train/test sets.
for set_ in augmentations:
random.shuffle(set_)
# Saves augmentations into a pickle file.
utils.store_data(augmentations, self.augmentations_file_path)
print('"augmentations" file finished')
# Creates Hdf5 database and save patches images, saving the patches if off by default.
self.save_images(augmentations, sets_with_labels, save=self.save_img)
def augment(self, sets, augmentations):
# For train and test lists.
for set_, augmentation_set in zip(sets, augmentations):
'''
Set: [('231___2_114_13_6.jpg', 13.4630136986) , ...]
[('Image name.jpg', Survival years), ...]
'''
current_img_idx = 0
for filename, labels in set_:
self.patches_per_file[filename] = 0
n = len(augmentation_set)
for config in self.sample_patches(filename):
config = (current_img_idx, ) + config
augmentation_set.append(config)
self.patches_per_file[filename] += 1
print('Patches per image: %s %s ' %
(filename, self.patches_per_file[filename]))
# If no new patches are created, remove image file from list and replace sets pickle.
# Possibilities?
# Useless image: most of the picture is white.
if n == len(augmentation_set):
del set_[current_img_idx]
utils.store_data(sets, self.sets_file_path)
print('"sets" updated (%s discarded)' % filename)
# Save augmentations in each iteration.
utils.store_data(augmentations, self.augmentations_file_path)
print('checkpoint saved')
current_img_idx += 1
def run(self):
# Getting lists of images for train and test.
# Train , Test
# [ [file1, file2, ...] , [file1, file2, ...] ]
sets_with_labels = self.get_sets()
# Gets augmentations if available, empty lists otherwise.
# Train , Test
# [ [file1, file2, ...] , [file1, file2, ...] ]
augmentations = self.get_augmentations(len(sets_with_labels))
# If the augmentation reference file already exists, don't run this again.
if augmentations is None:
augmentations = [[] for _ in range(len(sets_with_labels))]
# Creates augmentation patches from the original images, it stores the information
# into pickle files.
self.augment(sets_with_labels, augmentations)
# Randomize patches for each of the train/test sets.
for set_ in augmentations:
random.shuffle(set_)
# Saves augmentations into a pickle file.
utils.store_data(augmentations, self.augmentations_file_path)
print('"augmentations" file finished')
# Creates Hdf5 database and save patches images, saving the patches if off by default.
self.save_images(augmentations, sets_with_labels, save=self.save_img)
def augment(self, sets, augmentations):
# For train and test lists.
for set_, augmentation_set in zip(sets, augmentations):
'''
Set: [('231___2_114_13_6.jpg', 13.4630136986) , ...]
[('Image name.jpg', Survival years), ...]
'''
current_img_idx = 0
for filename, labels in set_:
self.patches_per_file[filename] = 0
n = len(augmentation_set)
for config in self.sample_patches(filename):
config = (current_img_idx,) + config
augmentation_set.append(config)
self.patches_per_file[filename] += 1
print('Patches per image: %s %s ' % (filename, self.patches_per_file[filename]))
# If no new patches are created, remove image file from list and replace sets pickle.
# Possibilities?
# Useless image: most of the picture is white.
if n == len(augmentation_set):
del set_[current_img_idx]
utils.store_data(sets, self.sets_file_path)
print('"sets" updated (%s discarded)' % filename)
# Save augmentations in each iteration.
utils.store_data(augmentations, self.augmentations_file_path)
print('checkpoint saved')
current_img_idx += 1
def get_sets(self):
try:
sets_with_labels = utils.load_data(self.sets_file_path)
print('"sets" file loaded')
except FileNotFoundError:
sets = self.split_data_into_sets([0.8, 0.2])
sets_with_labels = self.append_labels(sets)
utils.store_data(sets_with_labels, self.sets_file_path)
print('"sets" file created')
return sets_with_labels
def get_sets(self):
try:
sets_with_labels = utils.load_data(self.sets_file_path)
print('"sets" file loaded')
except FileNotFoundError:
sets = self.split_data_into_sets([0.8, 0.2])
sets_with_labels = self.append_labels(sets)
utils.store_data(sets_with_labels, self.sets_file_path)
print('"sets" file created')
return sets_with_labels
