Python object_detection.utils.shape_utils.clip_tensor() Examples
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Example #1
Source File: shape_utils_test.py From Traffic-Rule-Violation-Detection-System with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #2
Source File: shape_utils_test.py From DOTA_models with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #3
Source File: shape_utils_test.py From MBMD with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #4
Source File: shape_utils_test.py From vehicle_counting_tensorflow with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #5
Source File: shape_utils_test.py From vehicle_counting_tensorflow with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #6
Source File: shape_utils_test.py From garbage-object-detection-tensorflow with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #7
Source File: shape_utils_test.py From ros_people_object_detection_tensorflow with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #8
Source File: shape_utils_test.py From object_detector_app with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #9
Source File: shape_utils_test.py From garbage-object-detection-tensorflow with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #10
Source File: shape_utils_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #11
Source File: shape_utils_test.py From HereIsWally with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #12
Source File: shape_utils_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #13
Source File: shape_utils_test.py From yolo_v2 with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #14
Source File: shape_utils_test.py From yolo_v2 with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #15
Source File: shape_utils_test.py From hands-detection with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #16
Source File: shape_utils_test.py From HereIsWally with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #17
Source File: shape_utils_test.py From Traffic-Rule-Violation-Detection-System with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #18
Source File: shape_utils_test.py From hands-detection with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #19
Source File: shape_utils_test.py From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #20
Source File: shape_utils_test.py From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #21
Source File: shape_utils_test.py From moveo_ros with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #22
Source File: shape_utils_test.py From tensorflow with BSD 2-Clause "Simplified" License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #23
Source File: shape_utils_test.py From tensorflow with BSD 2-Clause "Simplified" License | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #24
Source File: shape_utils_test.py From moveo_ros with MIT License | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #25
Source File: shape_utils_test.py From Gun-Detector with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #26
Source File: shape_utils_test.py From Gun-Detector with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #27
Source File: shape_utils_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #28
Source File: shape_utils_test.py From ros_tensorflow with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #29
Source File: shape_utils_test.py From ros_tensorflow with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_tensor_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, tf.constant(2)) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, tf.constant(2)) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, tf.constant(2)) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, tf.constant(2)) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)
Example #30
Source File: shape_utils_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 6 votes |
def test_pad_or_clip_tensor_using_integer_input(self): t1 = tf.constant([1], dtype=tf.int32) tt1 = shape_utils.pad_or_clip_tensor(t1, 2) t2 = tf.constant([[0.1, 0.2]], dtype=tf.float32) tt2 = shape_utils.pad_or_clip_tensor(t2, 2) t3 = tf.constant([1, 2, 3], dtype=tf.int32) tt3 = shape_utils.clip_tensor(t3, 2) t4 = tf.constant([[0.1, 0.2], [0.2, 0.4], [0.5, 0.8]], dtype=tf.float32) tt4 = shape_utils.clip_tensor(t4, 2) self.assertEqual(2, tt1.get_shape()[0]) self.assertEqual(2, tt2.get_shape()[0]) self.assertEqual(2, tt3.get_shape()[0]) self.assertEqual(2, tt4.get_shape()[0]) with self.test_session() as sess: tt1_result, tt2_result, tt3_result, tt4_result = sess.run( [tt1, tt2, tt3, tt4]) self.assertAllEqual([1, 0], tt1_result) self.assertAllClose([[0.1, 0.2], [0, 0]], tt2_result) self.assertAllEqual([1, 2], tt3_result) self.assertAllClose([[0.1, 0.2], [0.2, 0.4]], tt4_result)