import organize_drawing_according_to_details_new import order_bounding_boxes_in_each_block import clustering_precomputed_dbscan import read_from_clustered_merged import regex_clean_new import organize_drawing_according_to_details_new import json import redis import sys def write_redis(uuid, result, db_params): db = redis.Redis(db_params) db.set(uuid, result) def main(uuid, filepath, db, eps): filename = order_bounding_boxes_in_each_block.pdf_to_html(uuid, filepath) #print(filename) result, number_blocks, number_words= order_bounding_boxes_in_each_block.get_bound_box(filename) ##get coordinates+text out of html file into array of arrays if eps == '0': if number_words > 500: eps = 7 else: eps = 1 #print(eps) isos, general_tol = order_bounding_boxes_in_each_block.extract_isos(result) print(general_tol) res = clustering_precomputed_dbscan.cluster_and_preprocess(result,eps) clean_arrays = read_from_clustered_merged.read("/home/bscheibel/PycharmProjects/dxf_reader/temporary/values_clusteredfrom_precomputed_dbscan.csv") tables = order_bounding_boxes_in_each_block.get_tables(clean_arrays) pretty = regex_clean_new.print_clean(clean_arrays) res, details_dict = organize_drawing_according_to_details_new.main_function(pretty, tables) #print(res) json_isos = json.dumps(isos) json_result = json.dumps(res) json_details =json.dumps(details_dict) write_redis(uuid+"tol", general_tol,db) write_redis(uuid+"dims", json_result, db) write_redis(uuid+"isos",json_isos, db) write_redis(uuid+"eps", str(number_blocks)+","+str(number_words), db) write_redis(uuid+"details",json_details ,db) #print(json_details) #print(redis.Redis('localhost').get(uuid+"dims")) #print(result) if __name__ == "__main__": uuid = sys.argv[1] filename = sys.argv[2] db = sys.argv[3] eps = sys.argv[4] main(uuid,filename, db, eps) #main("33333", "/home/bscheibel/PycharmProjects/dxf_reader/drawings/5152166_Rev04.pdf", "localhost",3)