Python models.default_encoder() Examples
The following are 10
code examples of models.default_encoder().
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Example #1
Source File: models_test.py From DOTA_models with Apache License 2.0 | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #2
Source File: models_test.py From yolo_v2 with Apache License 2.0 | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #3
Source File: models_test.py From Gun-Detector with Apache License 2.0 | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #4
Source File: models_test.py From hands-detection with MIT License | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #5
Source File: models_test.py From object_detection_kitti with Apache License 2.0 | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #6
Source File: models_test.py From object_detection_with_tensorflow with MIT License | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #7
Source File: models_test.py From HumanRecognition with MIT License | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #8
Source File: models_test.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #9
Source File: models_test.py From models with Apache License 2.0 | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))
Example #10
Source File: models_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
def _testEncoder(self, batch_norm_params=None, channels=1): images = tf.to_float(np.random.rand(10, 28, 28, channels)) with self.test_session() as sess: end_points = models.default_encoder( images, 128, batch_norm_params=batch_norm_params) sess.run(tf.global_variables_initializer()) private_code = sess.run(end_points['fc3']) self.assertEqual(private_code.shape, (10, 128)) self.assertTrue(np.any(private_code)) self.assertTrue(np.all(np.isfinite(private_code)))