"""config.ini を読み込み、CONFIG 辞書データを返します.
この関数は、ConfigParser モジュールを使用して 'config.ini' ファイルを読み込み、その内容を辞書として返します。
Returns:
dict: 設定データを含む CONFIG 辞書。
Note:
config.ini ファイルについては以下を参照してください:
https://github.com/yKesamaru/FACE01_DEV/blob/master/docs/config_ini.md#about-configini-file
詳細については `config_ini.md <..docs/config_ini.md>`_ を参照してください。
'config.ini' は FACE01 の設定ファイルであり、Python の ConfigParser モジュールを使用しています。[DEFAULT] セクションは標準のデフォルト値を指定しており、この設定は例です。
'config.ini' を修正する前に、ConfigParser モジュールに精通している必要があります。ConfigParser モジュールについては `ConfigParser module documentation <https://docs.python.org/3/library/configparser.html>`_ を参照してください。
各セクションは [DEFAULT] セクションから継承されます。したがって、各セクションでは [DEFAULT] を上書きする項目（キーと値）のみを指定してください。
.. image:: ../docs/img/About_config_ini_file.png
:scale: 50%
:alt: config_ini.md
"""
import os
from configparser import ConfigParser
from datetime import datetime
from traceback import format_exc
from typing import Dict, List, Tuple
import numpy as np
import numpy.typing as npt
from face01lib.Calc import Cal
from face01lib.load_preset_image import LoadPresetImage
from face01lib.LoadImage import LoadImage
from face01lib.logger import Logger
from face01lib.video_capture import VidCap # py
vid = VidCap()
# import .vidCap as video_capture # so
[ドキュメント]
class Initialize:
"""Initialize class.
Load config.ini, return Dict style.
"""
def __init__(
self,
section: str = 'DEFAULT',
log_level: str = 'info'
) -> None:
"""init.
Args:
section (str, optional): Specify section which is defined in config.ini. Defaults to 'DEFAULT'.
log_level (str, optional): Receive log level value. Defaults to 'info'.
"""
self.section = section
self.log_level: str = log_level
# Setup logger: common way
import os.path
name: str = __name__
dir: str = os.path.dirname(__file__)
parent_dir, _ = os.path.split(dir)
self.logger = Logger(self.log_level).logger(name, parent_dir)
self.parent_dir: str = parent_dir
def _configure(self) -> Dict:
"""Load conf.ini and return conf_dict dictionary.
Args:
self
Returns:
Dict: conf_dict
NOTE:
deep_learning_model:
0:dlib_face_recognition_resnet_model_v1.dat,
1:JAPANESE_FACE_V1.onnx,
2:mobilefacenet.onnx
Default: 0 (dlib_face_recognition_resnet_model_v1.dat)
"""
preset_face_imagesDir: str = f'{self.parent_dir}/preset_face_images/'
os.chdir(self.parent_dir)
try:
conf: ConfigParser = ConfigParser()
success = conf.read('config.ini', 'utf-8')
# dict作成
conf_dict: Dict = {
'headless': conf.getboolean(self.section, 'headless'),
'deep_learning_model': int(conf.get(self.section, 'deep_learning_model')),
'anti_spoof': conf.getboolean(self.section, 'anti_spoof'),
'output_debug_log': conf.getboolean(self.section, 'output_debug_log'),
'number_of_crops': int(conf.get(self.section, 'number_of_crops')),
'log_level': conf.get(self.section, 'log_level'),
'set_width': int(conf.get(self.section, 'set_width')),
'similar_percentage': float(conf.get(self.section, 'similar_percentage')),
'jitters': int(conf.get(self.section, 'jitters')),
'preset_face_images_jitters': int(conf.get(self.section, 'preset_face_images_jitters')),
'preset_face_imagesDir': preset_face_imagesDir,
'upsampling': int(conf.get(self.section, 'upsampling')),
'mode': conf.get(self.section, 'mode'),
'frame_skip': int(conf.get(self.section, 'frame_skip')),
'number_of_people': int(conf.get(self.section, 'number_of_people')),
'use_pipe': conf.getboolean(self.section, 'use_pipe'),
'model_selection': int(conf.get(self.section, 'model_selection')),
'min_detection_confidence': float(conf.get(self.section, 'min_detection_confidence')),
'person_frame_face_encoding': conf.getboolean(self.section, 'person_frame_face_encoding'),
'same_time_recognize': int(conf.get(self.section, 'same_time_recognize')),
'set_area': conf.get(self.section, 'set_area'),
'movie': conf.get(self.section, 'movie'),
'user': conf.get(self.section, 'user'),
'passwd': conf.get(self.section, 'passwd'),
'rectangle': conf.getboolean(self.section, 'rectangle'),
'target_rectangle': conf.getboolean(self.section, 'target_rectangle'),
'draw_telop_and_logo': conf.getboolean(self.section, 'draw_telop_and_logo'),
'default_face_image_draw': conf.getboolean(self.section, 'default_face_image_draw'),
'show_overlay': conf.getboolean(self.section, 'show_overlay'),
'alpha': float(conf.get(self.section, 'alpha')),
'show_percentage': conf.getboolean(self.section, 'show_percentage'),
'show_name': conf.getboolean(self.section, 'show_name'),
'crop_face_image': conf.getboolean(self.section, 'crop_face_image'),
'frequency_crop_image': int(conf.get(self.section, 'frequency_crop_image')),
'crop_with_multithreading': conf.getboolean(self.section, 'crop_with_multithreading'),
'Python_version': conf.get(self.section, 'Python_version'),
'cpu_freq': conf.get(self.section, 'cpu_freq'),
'cpu_count': conf.get(self.section, 'cpu_count'),
'memory': conf.get(self.section, 'memory'),
'gpu_check': conf.getboolean(self.section, 'gpu_check'),
'calculate_time': conf.getboolean(self.section, 'calculate_time'),
'show_video': conf.getboolean(self.section, 'show_video'),
'RootDir': self.parent_dir,
'detect_eye_blinks': conf.getboolean(self.section, 'detect_eye_blinks'),
'number_of_blinks': int(conf.get(self.section, 'number_of_blinks')),
'EAR_THRESHOLD_CLOSE': float(conf.get(self.section, 'EAR_THRESHOLD_CLOSE')),
'EAR_THRESHOLD_OPEN': float(conf.get(self.section, 'EAR_THRESHOLD_OPEN')),
}
return conf_dict
except:
self.logger.warning("config.ini 読み込み中にエラーが発生しました")
self.logger.exception("conf_dictが正常に作成できませんでした")
self.logger.warning("以下のエラーをシステム管理者様へお伝えください")
self.logger.warning("-" * 20)
self.logger.warning(format_exc(limit=None, chain=True))
self.logger.warning("-" * 20)
self.logger.warning("終了します")
exit(1)
# Initialize variables, load images
[ドキュメント]
def initialize(
self,
) -> Dict:
"""Initialize values.
Returns:
Dict: CONFIG
Dictionary of initialized preferences
Example:
.. code-block:: python
CONFIG: Dict = Initialize("SECTION").initialize()
"""
self.conf_dict: Dict = self._configure()
headless: bool = self.conf_dict["headless"]
# overwrite `log_level`
self.conf_dict['log_level'] = self.log_level
known_face_encodings: List[np.ndarray]
known_face_names: List[str]
known_face_encodings, known_face_names = \
LoadPresetImage().load_preset_image(
self.conf_dict["deep_learning_model"],
self.conf_dict["RootDir"],
self.conf_dict["preset_face_imagesDir"]
)
# debug: 同一ファイルだった。
# with open(f'{self.parent_dir}/npKnownなし.txt', 'w') as f:
# f.write(str(known_face_names))
# f.write(str(known_face_encodings))
# print(f"known_face_names: {type(known_face_names)}")
# print(f"known_face_encodings: {type(known_face_encodings)}")
# set_width,fps,height,width,set_height
set_width: int
fps: int
height: int
width: int
set_height: int
set_width, fps, height, width, set_height = \
vid.return_movie_property(
self.conf_dict["set_width"],
vid.return_vcap(self.conf_dict["movie"])
)
tolerance: float = Cal().to_tolerance(
self.conf_dict["similar_percentage"],
self.conf_dict["deep_learning_model"]
)
LoadImage_obj: LoadImage = LoadImage(
headless,
self.conf_dict
)
rect01_png: npt.NDArray[np.uint8]
rect01_NG_png: List[npt.NDArray[np.uint8]]
rect01_REAL_png: npt.NDArray[np.uint8]
rect01_SPOOF_png: npt.NDArray[np.uint8]
rect01_CANNOT_DISTINCTION_png: npt.NDArray[np.uint8]
resized_telop_image: npt.NDArray[np.uint8]
cal_resized_telop_nums: Tuple[int, int,
int, int, np.ndarray, np.ndarray]
resized_logo_image: npt.NDArray[np.uint8]
cal_resized_logo_nums: Tuple[int, int,
int, int, np.ndarray, np.ndarray]
load_unregistered_face_image: bool
telop_image: npt.NDArray[np.uint8]
logo_image: npt.NDArray[np.uint8]
unregistered_face_image: npt.NDArray[np.uint8]
rect01_png, rect01_NG_png, rect01_REAL_png, rect01_SPOOF_png, rect01_CANNOT_DISTINCTION_png, resized_telop_image, cal_resized_telop_nums, resized_logo_image, \
cal_resized_logo_nums, load_unregistered_face_image, telop_image, logo_image, unregistered_face_image = \
LoadImage_obj.LI(set_height, set_width)
# 日付時刻算出
date = datetime.now().strftime("%Y,%m,%d,%H,%M,%S,%f") # %f-> マイクロ秒
# 辞書作成
init_dict: Dict
if headless is False:
init_dict = {
'known_face_encodings': known_face_encodings,
'known_face_names': known_face_names,
'date': date,
'rect01_png': rect01_png,
'rect01_NG_png': rect01_NG_png,
'rect01_REAL_png': rect01_REAL_png,
'rect01_SPOOF_png': rect01_SPOOF_png,
'rect01_CANNOT_DISTINCTION_png': rect01_CANNOT_DISTINCTION_png,
'telop_image': telop_image,
'resized_telop_image': resized_telop_image,
'cal_resized_telop_nums': cal_resized_telop_nums,
'logo_image': logo_image,
'cal_resized_logo_nums': cal_resized_logo_nums,
'unregistered_face_image': unregistered_face_image,
'height': height,
'width': width,
'set_height': set_height,
'tolerance': tolerance,
'default_face_image_dict': {}
}
elif headless is True:
init_dict = {
'known_face_encodings': known_face_encodings,
'known_face_names': known_face_names,
'date': date,
'height': height,
'width': width,
'set_height': set_height,
'tolerance': tolerance,
'default_face_image_dict': {}
}
# 辞書結合
CONFIG: Dict = {**init_dict, **self.conf_dict}
# ヘッドレス実装
# if headless == True:
# CONFIG['rectangle'] = False
# CONFIG['target_rectangle'] = False
# CONFIG['show_video'] = False
# CONFIG['default_face_image_draw'] = False
# CONFIG['show_overlay'] = False
# CONFIG['show_percentage'] = False
# CONFIG['show_name'] = False
# CONFIG['draw_telop_and_logo'] = False
# CONFIG['person_frame_face_encoding'] = False
# CONFIG['headless'] = True
os.chdir(CONFIG["RootDir"])
return CONFIG