face reader, face detection and identification extractors

1 files changed, 62 insertions, 0 deletions

diff --git a/test/extractor/image/face/test_detect.py b/test/extractor/image/face/test_detect.py
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+++ b/test/extractor/image/face/test_detect.py
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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 ##