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 save_orig_char(im, char):
"""
保存生成的原始图片
:param im:
:param char:
:return:
"""
dir_path = GENERATE_ORIG_CHAR_DIE_PATH + char + '/'
create_dir(dir_path)
path = dir_path + str(uuid.uuid4()) + '.jpg'
save_img(im, path)
def __init__(self, mode='console', log_path=None):
"""
:param mode: console or file
:param log_path:
"""
assert mode in ['console', 'file']
self.__mode = mode
if log_path is None:
dir_path = combine_file_path('logs')
create_dir(dir_path)
log_path = os.path.join(dir_path, 'log.log')
if not os.path.exists(path=log_path):
file = open(log_path, encoding='utf8', mode='w')
file.close()
self.__log_path = log_path
2018/8/31:
-------------------------------------------------
"""
import json
import os
from utility.file_io_utility import read_all_content
from utility.file_path_utility import get_all_file_from_dir, create_dir
from xml.dom.minidom import Document
__author__ = 'li'
result_dir_path = 'C:/Users\lr\Desktop/123'
result_paths = get_all_file_from_dir(result_dir_path)
save_annotation_dir = './xml/'
create_dir(save_annotation_dir)
def load_result(result_paths):
"""
load result
:param result_paths:
:return:
"""
for p in result_paths:
if p.find('txt') > 0:
with open(p, mode='r', encoding='utf8') as file:
lines = file.readlines()
if len(lines) == 0:
continue
dir_path, file_name = os.path.split(p)
__author__ = 'li'
upload_path = 'F:/BaiduNetdiskDownload/upload/'
annotation_path = 'F:\BaiduNetdiskDownload/annotation'
img_path = 'F:\BaiduNetdiskDownload/uuid_image'
def load_map(path):
paths = get_all_file_from_dir(path)
map = {}
for p in paths:
dir_, name = os.path.split(p)
key = name.split('.')[0]
map[key] = p
return map
img_map = load_map(img_path)
anns_map = load_map(annotation_path)
for k in img_map.keys():
dir_name = upload_path + str(k[0])
img_dir = dir_name + '/img/'
ann_dir = dir_name + '/ann/'
create_dir(img_dir)
create_dir(ann_dir)
if k in anns_map.keys():
shutil.copy(img_map[k], img_dir + str(k) + '.jpg')
shutil.copy(anns_map[k], ann_dir + str(k) + '.xml')
pass
-------------------------------------------------
"""
import base64
import json
import math
import os
import cv2
from chinese_project.move_file.rename_file_md5 import GetFileMd5
from llib.cv_utility.image_opt_utility import read_image, write_image
from utility.file_io_utility import read_all_content
from utility.file_path_utility import get_all_file_from_dir, create_dir
import numpy as np
JSON_DIR = '/data/data/dangerous_bb/tt/project/daokou/data/json/'
TRAINING_DATA_DIR = 'G:/tmp/txt/'
create_dir(TRAINING_DATA_DIR)
enlarge_radio = 0.9
def save_image(image_str, i, file_name):
if enlarge_radio == 1:
image_path = TRAINING_DATA_DIR + file_name.replace('.json',
'') + '.jpg'
else:
image_path = TRAINING_DATA_DIR + file_name.replace('.json', '') + \
str(enlarge_radio).replace('.', '_') + '.jpg'
fh = open(image_path, "wb")
fh.write(base64.b64decode(image_str))
fh.close()
img = read_image(image_path)