import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
OUTPUT_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'data', 'output'))
INPUT_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'data',
'input'))
MASK_RCNN_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'model', 'mask_rcnn_model'))
MODEL_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'model'))
MODEL_PATH = os.path.join(MODEL_DIR, 'bg_removal_graph.pb')
MIN_RATIO = 0.1
HSV_THRESH = 40
SUB_IMG_COUNTS = 20
SUB_IMG_MARGIN = 5
import os from utils.folder_file_manager import make_directory_if_not_exists CUR_DIR = os.path.dirname(os.path.abspath(__file__)) JOB_TITLE_CSV_PATH = os.path.join(CUR_DIR, 'job_titles.csv') TRAIN_DATA_CSV_PATH = os.path.join(CUR_DIR, 'train.csv') TEST_DATA_CSV_PATH = os.path.join(CUR_DIR, 'test.csv') MODEL_DIR_PATH = make_directory_if_not_exists(os.path.join(CUR_DIR, 'utils', 'model')) MODEL_PATH = os.path.join(MODEL_DIR_PATH, "job_title_model.joblib") CORPUS_PATH = os.path.join(MODEL_DIR_PATH, 'corpus.txt') PREDICT_CSV_PATH = os.path.join(CUR_DIR, 'predict.csv') TEST_RATIO = 0.3 PREDICTION_ONLY = True PREDICTION_ONE_TITLE = True NEW_PREDICTION_PATH = ""
import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
LP_MODEL_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'model', 'models', 'lp_detection_model'))
ARABIC_LETTER_MODEL_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'model', 'models',
'arabic_handwritten_model'))
LP_CONFIG_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'model', 'cfg'))
LP_NAMES_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'model', 'names'))
ARABIC_LETTER_MODEL_WEIGHTS = os.path.join(ARABIC_LETTER_MODEL_DIR,
'weights.hdf5')
ARABIC_LETTER_MODEL = os.path.join(ARABIC_LETTER_MODEL_DIR, 'letter_model.h5')
ARABIC_LETTER_MODEL_YAML = os.path.join(ARABIC_LETTER_MODEL_DIR,
'letter_model.yaml')
ARABIC_DIGITS_MODEL = os.path.join(ARABIC_LETTER_MODEL_DIR, 'digit_model.h5')
ARABIC_DIGITS_YAML = os.path.join(ARABIC_LETTER_MODEL_DIR, 'digit_model.yaml')
DETECT_FRAME_PATH = ""
HANDWRITTEN_DIGITS_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahdd1/csvTestImages 10k x 784.zip"
RESIZE_HANDWRITTEN_DIGITS_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahdd1/csvTestImages 10k x 1024.csv"
HANDWRITTEN_DIGITS_TRAINING_IMAGE_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahdd1/csvTrainImages 60k x 1024.zip"
HANDWRITTEN_DIGITS_TRAINING_LABEL_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahdd1/csvTrainLabel 60k x 1.zip"
HANDWRITTEN_DIGITS_TESTING_IMAGE_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahdd1/csvTestImages 10k x 1024.zip"
HANDWRITTEN_DIGITS_TESTING_LABEL_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahdd1/csvTestLabel 10k x 1.zip"
HANDWRITTEN_LETTERS_TRAINING_IMAGE_PATH = "/media/mensa/Data/Task/EgyALPR/data/ahcd1/csvTrainImages 13440x1024.zip"
import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
MODEL_DIR = os.path.join(CUR_DIR, 'utils', 'model')
DATA_DIR = os.path.join(CUR_DIR, 'data')
TRAIN_DATA_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'train_data'))
FEATURE_CSV_FILE = os.path.join(TRAIN_DATA_DIR, 'feature.csv')
LABEL_CSV_FILE = os.path.join(TRAIN_DATA_DIR, 'label.csv')
CLASSIFICATION_MODEL = os.path.join(MODEL_DIR, 'classifier.pkl')
INCEPTION_URL = 'http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz'
import os
import configparser
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
INPUT_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'input'))
OUTPUT_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'output'))
PDF_IMAGES_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'pdf_images'))
SAMPLE_DIR = os.path.join(CUR_DIR, 'utils', 'sample')
SAMPLE_PDF = os.path.join(SAMPLE_DIR, 'sample.pdf')
AWS_PDF_STORAGE_BUCKET = 'occupant-pdf'
AWS_RESULT_OBJECT = "inbox/ODPS"
CONFIG_FILE = os.path.join(CUR_DIR, 'config.cfg')
params = configparser.ConfigParser()
params.read(CONFIG_FILE)
json_file = params.get("DEFAULT", "json_name")
VISION_CREDENTIAL_PATH = os.path.join(CUR_DIR, 'utils', 'credential',
f'{json_file}')
PROCESSED_FILE = os.path.join(CUR_DIR, 'utils', 'processed_files.txt')
FONT_SIZE = 0.6
FONT_WIDTH = 2
OCCUPANT_SPACING = 83
MOTORIST_SPACING = 145
REPORT_TEXT_POSITION = {
"report_number": [470, 35],
import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
IMAGE_RESULT_DIR = make_directory_if_not_exists(os.path.join(
CUR_DIR, 'result'))
WEIGHTS_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'utils', 'weights'))
TEST_DATA_DIR = os.path.join(CUR_DIR, 'test_data')
POSITIVE_DIR = os.path.join(TEST_DATA_DIR, 'positives')
NEGATIVE_DIR = os.path.join(TEST_DATA_DIR, 'HealthyAll')
SUB_NEGATIVE_DIR = os.path.join(CUR_DIR, 'sub_healthy')
ROC_CURVE_PATH = os.path.join(IMAGE_RESULT_DIR, 'roc_curve.png')
NOISY_VS_TISSUE_MODEL_PATH = os.path.join(CUR_DIR, 'utils',
'NoisyVSTissueModel.h5')
GENERATOR_WEIGHT = os.path.join(WEIGHTS_DIR, 'generator_127.h5')
DISCRIMINATOR_WEIGHT = os.path.join(WEIGHTS_DIR, 'discriminator_127.h5')
OPT_THRESH_PATH = os.path.join(IMAGE_RESULT_DIR, 'opt_threshold.txt')
OPT_RESULT_CSV = os.path.join(IMAGE_RESULT_DIR, 'result.csv')
PROCESS_CSV = os.path.join(IMAGE_RESULT_DIR, 'process_thresh_fpr_tpr.csv')
MAX_GAN_LOSS_MSE = 11
MIN_GAN_LOSS_MSE = 2
OPT_THRESH = 0.0005
LOCAL = True
if LOCAL:
TEMP_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'temp'))
import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
PDF_IMAGES_DIR = make_directory_if_not_exists(os.path.join('/tmp', 'pdf_images'))
CONFIG_FILE = os.path.join(CUR_DIR, 'config.cfg')
PDF_RET = False
import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
ORIGIN_IMG_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'data', 'origin_images'))
TEST_IMG_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'data', 'test_images'))
MODEL_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'data',
'model'))
MYSQL_CREDENTIAL_PATH = os.path.join(CUR_DIR, 'utils', 'mysql_credential.json')
INCEPTION_URL = 'http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz'
# IMG_SITE_DIR = os.path.join(CUR_DIR, 'images', 'original')
IMG_SITE_DIR = os.path.join('/opt', 'lampp', 'htdocs', 'server', 'images',
'original')
FLANN_INDEX_KDTREE = 0
STANDARD_WIDTH = 800
STANDARD_HEIGHT = 600
SM_THRESH = 0.8
import os
from utils.folder_file_manager import make_directory_if_not_exists
CUR_DIR = os.path.dirname(os.path.abspath(__file__))
MODEL_DIR = os.path.join(CUR_DIR, 'utils', 'model')
INPUT_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'input'))
VIDEO_INPUT_DIR = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'video_input'))
UPLOAD_FOLDER = make_directory_if_not_exists(
os.path.join(CUR_DIR, 'static', 'uploads'))
CAFFEMODEL_PATH = os.path.join(MODEL_DIR, 'SSD_MobileNet.caffemodel')
PROTOTXT_PATH = os.path.join(MODEL_DIR, 'SSD_MobileNet_prototxt.txt')
YOLO_WEIGHT_PATH = os.path.join(MODEL_DIR, 'yolov3.weights')
YOLO_CONFIG_PATH = os.path.join(MODEL_DIR, 'yolov3.cfg')
YOLO_COCO_PATH = os.path.join(MODEL_DIR, 'coco.names')
PB_MODEL_PATH = os.path.join(MODEL_DIR, 'frcnn_inception_v2.pb')
PB_TEXT_PATH = os.path.join(MODEL_DIR, 'frcnn_inception_v2_graph.pbtxt')
DETECT_CONFIDENCE = 0.3
OVERLAP_THRESH = 0.5
SAFE_DISTANCE = 200
FOCUS_LENGTH = 615
SERVER_HOST = "0.0.0.0"
SERVER_PORT = 5000
GPU = True
LOCAL = True
import os from utils.folder_file_manager import make_directory_if_not_exists CUR_DIR = os.path.dirname(os.path.abspath(__file__)) PDF_IMAGES_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'pdf_images')) PDF_UPLOAD_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'static', 'upload')) OUTPUT_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'output')) ARCHIVE_DIR = make_directory_if_not_exists(os.path.join(CUR_DIR, 'archive_dir')) INVOICE_DIR = os.path.join(CUR_DIR, 'invoice_dir') VISION_CREDENTIAL_PATH = os.path.join(CUR_DIR, 'utils', 'credential', 'tonal-studio-295208-5eedce5679d0.json') ROTATION_Y_THREAD = 200 Y_BIND_THREAD = 10 FRAME_THRESH_EMPHASIZE = 51 FRAME_THRESH_NOISE = 6 THREADING_ITEM = 2 LOCAL = True SERVER_HOST = "0.0.0.0" SERVER_PORT = 5000 DB_USERNAME = "******" DB_PASSWORD = "******" DB_NAME = "invoice_db" DB_HOST = "localhost"
