def transform_store_from_numpy(self,
images,
labels_values,
labels_names,
labels_classes=None,
lmdb_dir='.data/',
category='training',
total_number_imgs=0,
file_idx=None):
create_if_not_exist(lmdb_dir)
num_images = images.shape[0]
lmdb_name = lmdb_dir + os.sep + '_{}'.format(category)
if file_idx is None:
index = 0
else:
index = file_idx * 10000
# print('Storing ' + str(num_images) + lmdb_dir + '_{}'.format(category))
if labels_classes is None:
for idx, (image, latents_val) in tqdm(enumerate(
zip(images, labels_values)),
total=num_images):
img = np.float32(image) / self.scaler
labels_dict = {}
for i, A in enumerate(labels_names):
labels_dict[A] = latents_val[i]
self.store_single_lmdb(index=index,
filename=lmdb_name,
img=img,
labels_dict=labels_dict,
num_images=total_number_imgs)
index = index + 1
else:
for idx, (image, latents_val, labels_class) in tqdm(
enumerate(zip(images, labels_values, labels_classes)),
total=num_images):
img = np.float32(image) / self.scaler
labels_dict = {}
for i, A in enumerate(labels_names):
labels_dict[f'{A}_value'] = latents_val[i]
labels_dict[f'{A}_class'] = labels_class[i]
self.store_single_lmdb(index=index,
filename=lmdb_name,
img=img,
labels_dict=labels_dict,
num_images=total_number_imgs)
index = index + 1
def transform_store(self,
image_dir,
labels_fn,
lmdb_dir='.data/',
category='training',
target_size=None,
color_mode='rgb'):
create_if_not_exist(lmdb_dir)
classes = list(self.image_lists.keys())
total_number_of_img = 0
for label_name in classes:
total_number_of_img += len(self.image_lists[label_name][category])
print('Total number of imgs for catagory ' + str(total_number_of_img))
num_class = len(classes)
class2id = dict(zip(classes, range(len(classes))))
id2class = dict((v, k) for k, v in class2id.items())
lmdb_index = 0
for label_name in classes:
num_images = len(self.image_lists[label_name][category])
print('Storing ' + str(num_images) + lmdb_dir + os.sep +
'into _{} from folder {}'.format(category, label_name))
for index, _ in enumerate(self.image_lists[label_name][category]):
img_path = get_file_path(self.image_lists, label_name, index,
image_dir, category)
img = img_to_array(load_img(img_path,
grayscale=color_mode
== 'grayscale',
target_size=target_size),
data_format=self.data_format) / self.scaler
label_dict = labels_fn(img_path)
name = lmdb_dir + os.sep + '_{}'.format(category)
lmdb_index += 1
self.store_single_lmdb(index=lmdb_index,
filename=name,
img=img,
labels_dict=label_dict,
num_images=total_number_of_img)