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# standard imports
import contextlib
import io
import os
import requests
import unittest
# bsie imports
from bsie.extractor import base
from bsie.reader.face import FaceExtract
from bsie.utils import bsfs, node as _node, ns
# objects to test
from bsie.extractor.image.face.detect import FaceDetect, bsf
## code ##
class TestFaceDetect(unittest.TestCase):
def setUp(self):
# download test image
target = os.path.join(os.path.dirname(__file__), 'testface1.jpg')
if not os.path.exists(target):
with open(target, 'wb') as ofile:
ans = requests.get('https://www.bsfs.io/testdata/iepahGee1uch5ahr3ic1.jpg')
ofile.write(ans.content)
def test_extract(self):
with contextlib.redirect_stderr(io.StringIO()): # NOTE: hide warnings from facenet_pytorch
# setup
rdr = FaceExtract()
ext = FaceDetect()
subject = _node.Node(ns.bsfs.Entity)
content = rdr(os.path.join(os.path.dirname(__file__), 'testface1.jpg'))
principals = set(ext.principals)
face = _node.Node(ns.bsn.Face, ucid='2a7203c1515e0caa66a7461452c0b4552f1433a613cb3033e59ed2361790ad45')
triples = list(ext.extract(subject, content, principals))
# principals is bse:face
self.assertSetEqual(principals, {ext.schema.predicate(ns.bse.face)})
# check triples
self.assertIn((subject, ns.bse.face, face), triples)
self.assertIn((face, bsf.x, 575.4721153898192), triples)
self.assertIn((face, bsf.y, 265.3955625), triples)
self.assertIn((face, bsf.width, 626.3928904791771), triples)
self.assertIn((face, bsf.height,858.6870625), triples)
# check embedding
emb = [o for s, p, o in triples if s == face and p == bsf.embedding]
self.assertEqual(len(emb), 1)
self.assertAlmostEqual(emb[0].sum(), -1.9049968)
# no triples on principal mismatch
self.assertListEqual(list(ext.extract(subject, content, set())), [])
# no triples on no content
self.assertListEqual(list(ext.extract(subject, [], principals)), [])
## main ##
if __name__ == '__main__':
unittest.main()
## EOF ##
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