def ocr_for_all_image():
path = "../static"
image_path_list = get_file_from_folder(path)
for image in image_path_list:
file_name = basename(image).split('.')[0] + ".txt"
file_text = ocr(image)
save_file(name=file_name, text=file_text, path="../Data/ocr_text/")
def create_empty_file():
path = "../static"
image_path_list = get_file_from_folder(path)
for image in image_path_list:
file_name = basename(image).split('.')[0]
f1 = open(f"../Data/correct_text/{file_name}.txt", "w")
f2 = open(f"../Data/ocr_text/{file_name}.txt", "w")
f1.close()
f2.close()
def get_problems():
def read_file(path="", _type="txt"):
file = open(path, "r", encoding="utf8")
data = file.read()
file.close()
return data
image_path_list = get_file_from_folder('./static')
result = {}
for image in image_path_list:
image_name = basename(image)
image_name_without_addition = image_name.split('.')[0]
image_path = f'http://localhost:3001/static/{image_name}'
image_ocr_text_file_path = f'./Data/ocr_text/{image_name_without_addition}.txt'
image_correct_text_file_path = f'./Data/correct_text/{image_name_without_addition}.txt'
image_nlp_mahad_ocr_text_file_path = f'./Data/nlp_ocr_text/mahad/{image_name_without_addition}.txt'
image_nlp_mahad_correct_text_file_path = f'./Data/nlp_correct_text/mahad/{image_name_without_addition}.txt'
image_nlp_mahrous_ocr_text_file_path = f'./Data/nlp_ocr_text/mahrous/{image_name_without_addition}.txt'
image_nlp_mahrous_correct_text_file_path = f'./Data/nlp_correct_text/mahrous/{image_name_without_addition}.txt'
image_solve_file_path = f'./Data/solve/{image_name_without_addition}.txt'
ocr_text = read_file(image_ocr_text_file_path)
correct_text = read_file(image_correct_text_file_path)
nlp_mahad_ocr_text = json.loads(read_file(image_nlp_mahad_ocr_text_file_path))
nlp_mahad_correct_text = json.loads(read_file(image_nlp_mahad_correct_text_file_path))
nlp_mahrous_ocr_text = json.loads(read_file(image_nlp_mahrous_ocr_text_file_path))
nlp_mahrous_correct_text = json.loads(read_file(image_nlp_mahrous_correct_text_file_path))
solve = json.loads(read_file(image_solve_file_path))
result[image_name_without_addition] = {
"correct_text": correct_text,
"ocr_text": ocr_text,
"image_path": image_path,
"image_name": image_name,
"nlp_mahad_ocr_text": nlp_mahad_ocr_text,
"nlp_mahad_correct_text": nlp_mahad_correct_text,
"nlp_mahrous_ocr_text": nlp_mahrous_ocr_text,
"nlp_mahrous_correct_text": nlp_mahrous_correct_text,
"solve": solve
}
return jsonify(result)
pass
import json
from ntpath import basename
from HELP.file_tool import get_file_from_folder
from SOLVE.solveTree import SolveTree
def main(data):
result = []
for item in data:
tree = SolveTree(item)
parse = tree.parser()
result.append(tree.parser())
return result
if __name__ == '__main__':
files = get_file_from_folder("../Data/nlp_correct_text/mahrous")
for path in files:
file_name = basename(path)
file = open(path, "r", encoding="utf8")
text = file.read()
file.close()
data = json.loads(text)
if "data" in data:
solve = main(data['data'])
with open(f'../Data/solve/{file_name}', 'w',
encoding="utf8") as json_file:
json.dump(solve, json_file)
data = [{
"type": "نص السوال" if i == 0 else f"{i} الطلب",
"line": array[i],
"keyword": array_arabic[i],
"symbols": array_symbols[i]
} for i in range(len(array))]
data = link_keyword_with_symbols(data)
data = [handle_special_cases(item) for item in data]
problem_type = problem_classification(data)
return {"data": data, "problem_type": problem_type}
if __name__ == '__main__':
ocr_files = get_file_from_folder("../Data/ocr_text")
correct_files = get_file_from_folder("../Data/correct_text")
for path in ocr_files:
file_name = basename(path)
ocr_file = open(path, "r", encoding="utf8")
ocr_text = ocr_file.read()
ocr_file.close()
ocr_json = main(ocr_text)
with open(f'../Data/nlp_ocr_text/mahrous/{file_name}',
'w',
encoding="utf8") as json_file:
json.dump(ocr_json, json_file)
for path in correct_files:
file_name = basename(path)
correct_file = open(path, "r", encoding="utf8")
correct_text = correct_file.read()