import body
import ip_preprocessing as pre
import ip_draw as draw
import file_utils as file
from CONFIG import Config
from MODEL import CNN
import cv2
import time
import glob
from os.path import join as pyjoin
# initialization
C = Config()
C.build_output_folders(False)
input_root = C.ROOT_INPUT
input_paths = glob.glob(pyjoin(input_root, '*.png'))
input_paths = sorted(input_paths, key=lambda x: int(x.split('\\')[-1][:-4])) # sorted by index
def save(index, org, binary, corners_block, corners_img, corners_compo, compos_class, corners_text):
out_img_gradient = pyjoin(C.ROOT_IMG_GRADIENT, index + '.png')
out_img_draw = pyjoin(C.ROOT_IMG_DRAWN, index + '.png')
out_img_clean = pyjoin(C.ROOT_IMG_CLEAN, index + '.png')
out_label = pyjoin(C.ROOT_LABEL, index + '.json')
# *** Step 7 *** post-processing: remove img elements from original image and segment into smaller size
img_clean = draw.draw_bounding_box(org, corners_img, color=(255, 255, 255), line=-1)
# draw results
draw_bounding = draw.draw_bounding_box_class(org, corners_compo, compos_class)
import time
import ocr_east as ocr
import ip
import merge
from CONFIG import Config
# choose functionality
is_ocr = True
is_ip = True
is_merge = True
# initialization
is_clip = False
C = Config()
C.build_output_folders(is_clip)
resize_by_height = 600
# set input root directory and sort all images by their indices
input_paths_img = glob.glob(pjoin(C.ROOT_INPUT, '*.jpg'))
input_paths_img = sorted(
input_paths_img,
key=lambda x: int(x.split('\\')[-1][:-4])) # sorted by index
# set the range of target inputs' indices
start_index = 24
end_index = 50
for input_path_img in input_paths_img:
index = input_path_img.split('\\')[-1][:-4]
if int(index) < start_index:
continue
if int(index) > end_index:
import glob
from os.path import join as pyjoin
# choose functionality
is_merge_img = True
is_shrink_img = True
is_detect_compo_in_img = True
is_classify = True
is_ocr = True
is_segment = False
is_save = True
is_clip = False
# initialization
C = Config()
C.build_output_folders(is_segment)
input_root = C.ROOT_INPUT
input_paths = glob.glob(pyjoin(input_root, '*.png'))
input_paths = sorted(
input_paths, key=lambda x: int(x.split('\\')[-1][:-4])) # sorted by index
CNN = CNN()
CNN.load()
# start image and end image
start_index = 20
end_index = 100
for input_path in input_paths:
index = input_path.split('\\')[-1][:-4]
if int(index) < start_index:
continue