VideoAnalysis/ontologyWorking.py

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Python
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2023-05-20 13:23:06 +04:00
import requests
def is_ontology_exists(uid, url):
list_ontologies = requests.get(url).json()['response']
for onto in list_ontologies:
if onto['uid'] == uid:
return False
return True
def get_list_sqwrl(uid, url):
return requests.get(url + f'{uid}/query/', verify=False).json()
def get_entity_square(results_ndarray_i):
square = float((results_ndarray_i[2] - results_ndarray_i[0]) *
(results_ndarray_i[3] - results_ndarray_i[1]))
return abs(square)
def get_request_data(entities, results_ndarray):
classroom = 'classroom'
object_properties = list()
data_properties = list()
for i, entity in enumerate(entities): # запись в лист имен объектов и присутствие
if (results_ndarray[:, -1] == i).sum() > 0: # если объект найден
object_properties.append({'domain': entity,
'property': 'locatedIn',
'range': classroom})
else:
object_properties.append({'domain': entity,
'property': 'notLocatedIn',
'range': classroom})
for i in range(results_ndarray.shape[0]):
data_properties.append({'domain': entities[int(results_ndarray[i, 5])],
'property': 'hasArea',
'value': get_entity_square(results_ndarray[i])})
data_properties.append({'domain': entities[int(results_ndarray[i, 5])],
'property': 'hasConfidence',
'value': float(results_ndarray[i, 4])})
return object_properties, data_properties