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- 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 = order_bounding_boxes_in_each_block.extract_isos(result)
- 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+"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)
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