def generate_segmented_data(xml_list, drawing_dir, drawing_segment_dir,
segment_params, text_xml_dir, symbol_dict,
include_text_as_class,
include_text_orientation_as_class,
drawing_resize_scale, prefix):
""" 폴더 내 원본 이미지 도면들을 분할하고 분할 정보를 리스트로 저장
Arguments:
xml_list (list): xml 파일 리스트
drawing_dir (string): 원본 도면 이미지가 존재하는 폴더
drawing_segment_dir (string): 분할된 이미지를 저장할 폴더
segment_params (list): 분할 파라메터 [가로 크기, 세로 크기, 가로 stride, 세로 stride]
text_xml_dir (string): text xml 파일의 폴더 (include_text_as_calss가 False면 사용하지 않음)
symbol_dict (dict): symbol 이름을 key로, id를 value로 갖는 dict
include_text_as_class (bool): text 데이터를 class로 추가할 것인지
drawing_resize_scale (float): 전체 도면 조정 스케일
prefix (string): train/val/test 중 하나. 이미지 저장 폴더명 생성에 필요
Return:
xml에 있는 전체 도면에서 분할된 도면의 전체 정보 [sub_img_name, symbol_name, xmin, ymin, xmax, ymax]
"""
entire_segmented_info = []
for xmlPath in xml_list:
print(f"Proceccing {xmlPath}...")
fname, ext = os.path.splitext(xmlPath)
if ext.lower() != ".xml":
continue
xmlReader = symbol_xml_reader(xmlPath)
img_filename, width, height, depth, object_list = xmlReader.getInfo()
for i in range(len(object_list)):
object_list[i][0] = symbol_dict[object_list[i][0].split("-")[0]]
img_file_path = os.path.join(drawing_dir, img_filename)
if include_text_as_class == True and os.path.exists(
os.path.join(text_xml_dir, os.path.basename(xmlPath))):
text_xml_reader_obj = text_xml_reader(
os.path.join(text_xml_dir, os.path.basename(xmlPath)))
_, _, _, _, txt_object_list = text_xml_reader_obj.getInfo()
segmented_objects_info = segment_images(
img_file_path, drawing_segment_dir, object_list,
txt_object_list, include_text_orientation_as_class,
symbol_dict, segment_params, drawing_resize_scale, prefix)
else:
segmented_objects_info = segment_images(
img_file_path, drawing_segment_dir, object_list, None, None,
symbol_dict, segment_params, drawing_resize_scale, prefix)
entire_segmented_info.extend(segmented_objects_info)
return entire_segmented_info
xml_dir = "D:/Test_Models/PNID/HyundaiEng/210518_Data/Symbol_XML"
drawing_img_dir = "D:/Test_Models/PNID/HyundaiEng/210518_Data/Drawing/JPG"
is_text_xml = False
xml_filenames = os.listdir(xml_dir)
entire_objects = []
for xml_filename in xml_filenames:
print(xml_filename)
name_only = xml_filename.split(".")[0]
xml_path = os.path.join(xml_dir, name_only + ".xml")
drawing_path = os.path.join(drawing_img_dir, name_only + ".jpg")
if is_text_xml == True:
text_xml_reader_obj = text_xml_reader(xml_path)
filename, width, height, depth, object_list = text_xml_reader_obj.getInfo(
)
else:
symbol_xml_reader_obj = symbol_xml_reader(xml_path)
filename, width, height, depth, object_list = symbol_xml_reader_obj.getInfo(
)
bbox = [[x[0], x[1], x[2], x[3] - x[1], x[4] - x[2]] for x in object_list]
entire_objects.extend(bbox)
unique_labels = set([x[0] for x in entire_objects])
occurences = {}
mean_diagonal_lengths = {}
for unique_label in unique_labels:
current_lables = [x[0] for x in entire_objects if x[0] == unique_label]
import os
import random
import pickle
from Common.pnid_xml import text_xml_reader
# Text XML에 존재하는 오류(앞뒤공백, multiline 박스 분할, 박스 크기 조정, 오류가 있는 object 제거)를 수정하여 다시 XML로 출력
text_xml_dir = "D:/Test_Models/PNID/HyundaiEng/210520_Data/_Text_XML_before_correction"
drawing_img_dir = "D:/Test_Models/PNID/HyundaiEng/210520_Data/Drawing/JPG"
processed_text_xml_dir = "D:/Test_Models/PNID/HyundaiEng/210520_Data/Text_XML/"
text_xmls = [os.path.join(text_xml_dir, x) for x in os.listdir(text_xml_dir)]
for text_xml in text_xmls:
print(text_xml)
text_xml_obj = text_xml_reader(text_xml)
text_xml_obj.error_correction(drawing_img_dir,
remove_spacing=True,
newline_separation=True,
remove_blank_pixel=False,
remove_blank_threshold=0.7,
margin=5,
remove_none_string=True,
remove_object_out_of_img=True)
filename = os.path.basename(text_xml)
text_xml_obj.write_xml(os.path.join(processed_text_xml_dir, filename))
def parse_test_gt_xmls(self):
""" Grount Truth를 저장하고 있는 xml들을 읽어서 coco json 형식과 dict 형식으로 반환
Return:
gt_json (dict): 모든 test 도면의 GT 정보가 coco 형식으로 저장된 dict
gt_result (dict): 모든 test 도면의 GT 정보가 image_name을 key로, bbox들이 value로 저장된 dict
"""
gt_json = {}
gt_result_json = {}
test_image_filenames = self.dt_result.keys()
images = []
annotations = []
categories = []
for sym_name, sym_id in self.symbol_dict.items():
categories.append({"id": sym_id, "name": sym_name})
image_id = 1
object_id = 1
for test_image_filename in test_image_filenames:
symbol_xml = symbol_xml_reader(
os.path.join(self.symbol_xml_dir,
f"{test_image_filename}.xml"))
filename, width, height, depth, object_list = symbol_xml.getInfo()
if self.include_text_as_class == True:
text_xml_path = os.path.join(self.text_xml_dir,
f"{test_image_filename}.xml")
if os.path.exists(text_xml_path) == True:
text_xml = text_xml_reader(text_xml_path)
_, _, _, _, text_object_list = text_xml.getInfo()
if self.include_text_orientation_as_class == True:
converted_text_object_list = [[
"text", x[1], x[2], x[3], x[4]
] for x in text_object_list if x[5] == 0]
converted_text_object_list += [[
"text_rotated", x[1], x[2], x[3], x[4]
] for x in text_object_list if x[5] == 90]
converted_text_object_list += [[
"text_rotated_45", x[1], x[2], x[3], x[4]
] for x in text_object_list if x[5] == 45]
else:
converted_text_object_list = [[
"text", x[1], x[2], x[3], x[4]
] for x in text_object_list]
object_list = object_list + converted_text_object_list
image = {
"file_name": f"{test_image_filename}.jpg",
"id": image_id,
"width": width,
"height": height # url, date 등 사용하지 않는 데이터 삭제
}
images.append(image)
annotations_per_image = []
for object in object_list: # [name, xmin, ymin, xmax, ymax]
x = object[1]
y = object[2]
width = object[3] - object[1]
height = object[4] - object[2]
name = object[0].split(sep='-', maxsplit=1)[0]
class_index = self.symbol_dict[name]
obj = {
"bbox": [x, y, width, height],
"category_id": class_index,
"image_id": image_id,
'id': object_id,
'area': width * height,
'segmentation': [],
"iscrowd": 0,
"ignore": 0,
}
annotations.append(obj)
annotations_per_image.append(obj)
object_id += 1
gt_result_json[test_image_filename] = annotations_per_image
image_id += 1
gt_json['annotations'] = annotations
gt_json['images'] = images
gt_json['categories'] = categories
return gt_json, gt_result_json