def main():
all_paths = get_all_files_under_directory(PARENT_DIR_PATH)
delete_paths = get_all_files_under_directory(DELETE_PATH)
all_keys = get_key(all_paths)
delete_keys = get_key(delete_paths)
index = 0
for key in all_keys:
if key not in delete_keys:
print(key)
shutil.copy(PARENT_DIR_PATH + key + '.jpg',
DES_PATH + str(index) + '_' + key + '.jpg')
index = index + 1
def get_name_set():
paths = get_all_files_under_directory('J:/waier_nei_jika/has_line')
names = set()
for path in paths:
_, name = os.path.split(path)
names.add(name)
return names
def main():
paths = get_all_files_under_directory(ORIGINAL_DIR_PATH)
for p in paths:
label = get_label(p)
print(label)
new_path = DES_PATH + label + '-' + str(uuid.uuid4()) + '.jpg'
shutil.copy(p, new_path)
def classification_images():
images_path = get_all_files_under_directory(ORIGINAL_PATH)
images_size = len(images_path)
for index in range(images_size):
try:
p = images_path[index]
if index % 100 == 0:
print(str(index) + '/' + str(images_size))
dir_path, image_name = os.path.split(p)
label = str(image_name.split('-')[0]).replace('#',
'').replace(' ', '')
if label == '':
dir_name = 'unrecognize'
else:
length = len(label)
dir_name = str(length)
new_path = os.path.join(DESTINATION_PATH, dir_name)
new_path = os.path.join(new_path, label)
create_dir(new_path)
# if label[0] == '4':
# label = label.replace('\\', '').replace('/', '')
md5 = GetFileMd5(p)
image_name = label + '-' + md5 + '.jpg'
des_path = os.path.join(new_path, image_name)
# if len(label) == 4:
shutil.copy(p, des_path)
except Exception as e:
print(e)
def get_fonts_paths():
"""
获取字体格式文件路径
:return:
"""
file_name = get_all_files_under_directory(FONTS_DIR_PATH)
fonts_paths = []
for i in range(CHOOSE_FONTS_SIZE):
files = random.choice(file_name)
fonts_paths.append(files)
return fonts_paths
def main():
mask_model = MaskModel()
dir_path = 'F:\dataset\detection_result/results/00f3d476-b62a-11e8-a9c6-11533fbcc673'
paths = get_all_files_under_directory(dir_path)
images = []
for p in paths:
if p.find('.png') > 0:
images.append(cv2.imread(p))
prece = mask_model.input_images_preprocess(images)
mask_model.build()
def main():
ver = 'E:\dataset\horizontal'
paths = get_all_files_under_directory(ver)
for index, path in enumerate(paths):
if index % 100 == 0:
print(index)
_, img_name = os.path.split(path)
label = img_name.split('-')[0]
img = cv2.imread(path)
if len(label) < 2:
continue
seg_horozontal(label, img)
def main():
ver = 'E:\dataset/vertical'
paths = get_all_files_under_directory(ver)
for index, path in enumerate(paths):
if index % 100 == 0:
print(index)
_, name = os.path.split(path)
label = name.split('-')[0]
if len(label) == 1:
continue
img = cv2.imread(path)
seg_vertical(label, img)
def __main():
img_paths = get_all_files_under_directory(SOURCE_DIR)
for index, path in enumerate(img_paths):
if '.jpg' not in path:
continue
if index % 10 == 0:
print(index)
_, name = os.path.split(path)
dir_name = name.split('_')[0]
md5_name = GetFileMd5(path)
des_path = DES_DIR + md5_name + '.jpg'
shutil.copy(path, des_path)
def load_mapping(image_dir_path):
"""
load name and path map
:param image_dir_path:
:return:
"""
imgs_path = get_all_files_under_directory(image_dir_path)
mapping = {}
for p in imgs_path:
_, name = os.path.split(p)
name = name.split('.')[0]
mapping[name] = p
return mapping
def get_black_images():
images_path = get_all_files_under_directory(ORIGINAL_PATH)
for p in images_path:
try:
img = cv2.imread(p)
mean = np.mean(np.mean(img, axis=0), axis=0)
if mean[0] < 40 and mean[1] < 40 and mean[2] < 40:
_, file_name = os.path.split(p)
print(file_name)
# os.remove(p)
shutil.move(p, BLACK_PATH + file_name)
except Exception as e:
print(e)
print(p)
def main():
img_dir = 'C:/Users/lr/Desktop/txt_inage'
img_paths = get_all_files_under_directory(img_dir)
txt_mapping = get_txt_mapping()
des_dir = 'C:/Users/lr/Desktop/genb/'
for path in img_paths:
_, name = os.path.split(path)
name = name.split('_____')[0]
if name not in txt_mapping:
print(name)
continue
new_name = get_uuid_str()
des_path = des_dir + new_name + '.jpg'
shutil.copy(path, des_path)
with open('result1.txt', mode='a', encoding='utf8') as file:
line = new_name + ' ' + txt_mapping[name] + '\n'
file.write(line)
def main():
source_dir = 'J:/car_door/original_image'
door_side_dir = 'J:/car_door/to_class/door_side/'
other_side_dir = 'J:/car_door/to_class/other_side/'
paths = get_all_files_under_directory(source_dir)
random.shuffle(paths)
for index, path in enumerate(paths):
_, name = os.path.split(path)
# if index < 4810:
# continue
if index % 10 == 0:
print(index)
if 'Pos' in name:
continue
print(path)
if 'Front' in name:
des_path = door_side_dir + name
shutil.copy(path, des_path)
elif 'Rear' in name:
des_path = other_side_dir + name
shutil.copy(path, des_path)
Description :
Author : 'li'
date： 2020/1/8
-------------------------------------------------
Change Activity:
2020/1/8:
-------------------------------------------------
"""
import os
import shutil
from utility.file_path_utility import get_all_files_under_directory
names = set()
with open('name.txt', mode='r', encoding='utf8') as file:
lines = file.readlines()
for line in lines:
line = line.strip()
if len(line) > 1:
names.add(line)
image_dir = 'J:/dangerous_mark/tocheck/dele/no/'
des_dir = 'C:/Users/lr/Desktop/tolael/'
image_paths = get_all_files_under_directory(image_dir)
for path in image_paths:
_, name = os.path.split(path)
name = name.replace('.jpg', '')
if name not in names:
print(name)
shutil.copy(path, des_dir + name + '.jpg')
def get_images_average_value(images_path):
"""
get images average values
:param images_path:
:return:
"""
images_size = len(images_path)
print('images size:' + str(images_size))
total_value = np.zeros((3,), dtype=np.float)
add_time = 0
for index in range(images_size):
if index % 100 == 0:
print(str(index) + '/' + str(images_size))
p = images_path[index]
img = cv.imread(p)
if img is not None:
aver = get_one_image_average_value(img)
total_value = np.add(total_value, aver)
add_time = add_time + 1
average_value = total_value / add_time
return average_value
if __name__ == '__main__':
dir_path = 'F:\BaiduNetdiskDownload/uuid_image'
paths = get_all_files_under_directory(dir_path)
average_value = get_images_average_value(paths)
print(average_value)
# -*- coding: utf-8 -*-
"""
-------------------------------------------------
File Name： get_all_file_path
Description :
Author : 'li'
date： 2020/1/18
-------------------------------------------------
Change Activity:
2020/1/18:
-------------------------------------------------
"""
import os
from llib.cv_utility.image_opt_utility import read_image, write_image
from utility.file_path_utility import get_all_files_under_directory
img_dir = 'J:/BaiduNetdiskDownload/0506'
des_path = 'J:/BaiduNetdiskDownload/plate_recognize/img/'
paths = get_all_files_under_directory(img_dir)
for path in paths:
_, name = os.path.split(path)
image = read_image(path)
write_image(des_path + name, image)
