Python object_detection.core.preprocessor.convert_class_logits_to_softmax() Examples
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code examples of object_detection.core.preprocessor.convert_class_logits_to_softmax().
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Example #1
| Source File: preprocessor_test.py From vehicle_counting_tensorflow with MIT License | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
expected_converted_multiclass_scores = [[[0.62245935, 0.37754068],
[0.5, 0.5], [1, 0]]]
with self.test_session() as sess:
(converted_multiclass_scores_) = sess.run([converted_multiclass_scores])
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #2
| Source File: preprocessor_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
expected_converted_multiclass_scores = [[[0.62245935, 0.37754068],
[0.5, 0.5], [1, 0]]]
with self.test_session() as sess:
(converted_multiclass_scores_) = sess.run([converted_multiclass_scores])
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #3
| Source File: preprocessor_test.py From MAX-Object-Detector with Apache License 2.0 | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
expected_converted_multiclass_scores = [[[0.62245935, 0.37754068],
[0.5, 0.5], [1, 0]]]
with self.test_session() as sess:
(converted_multiclass_scores_) = sess.run([converted_multiclass_scores])
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #4
| Source File: preprocessor_test.py From Accident-Detection-on-Indian-Roads with GNU Affero General Public License v3.0 | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
expected_converted_multiclass_scores = [[[0.62245935, 0.37754068],
[0.5, 0.5], [1, 0]]]
with self.test_session() as sess:
(converted_multiclass_scores_) = sess.run([converted_multiclass_scores])
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #5
| Source File: preprocessor_test.py From g-tensorflow-models with Apache License 2.0 | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
expected_converted_multiclass_scores = [[[0.62245935, 0.37754068],
[0.5, 0.5], [1, 0]]]
with self.test_session() as sess:
(converted_multiclass_scores_) = sess.run([converted_multiclass_scores])
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #6
| Source File: preprocessor_test.py From models with Apache License 2.0 | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
def graph_fn():
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
return converted_multiclass_scores
converted_multiclass_scores_ = self.execute_cpu(graph_fn, [])
expected_converted_multiclass_scores = [[0.62245935, 0.37754068],
[0.5, 0.5],
[1, 0]]
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #7
| Source File: preprocessor_test.py From multilabel-image-classification-tensorflow with MIT License | 6 votes |
|
def testConvertClassLogitsToSoftmax(self):
multiclass_scores = tf.constant(
[[1.0, 0.0], [0.5, 0.5], [1000, 1]], dtype=tf.float32)
temperature = 2.0
converted_multiclass_scores = (
preprocessor.convert_class_logits_to_softmax(
multiclass_scores=multiclass_scores, temperature=temperature))
expected_converted_multiclass_scores = [[[0.62245935, 0.37754068],
[0.5, 0.5], [1, 0]]]
with self.test_session() as sess:
(converted_multiclass_scores_) = sess.run([converted_multiclass_scores])
self.assertAllClose(converted_multiclass_scores_,
expected_converted_multiclass_scores)
Example #8
| Source File: preprocessor_builder_test.py From vehicle_counting_tensorflow with MIT License | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #9
| Source File: preprocessor_builder_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #10
| Source File: preprocessor_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #11
| Source File: preprocessor_builder_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #12
| Source File: preprocessor_builder_test.py From MAX-Object-Detector with Apache License 2.0 | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #13
| Source File: preprocessor_builder_test.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #14
| Source File: preprocessor_builder_test.py From models with Apache License 2.0 | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
Example #15
| Source File: preprocessor_builder_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
|
def test_build_normalize_image_convert_class_logits_to_softmax(self):
preprocessor_text_proto = """
convert_class_logits_to_softmax {
temperature: 2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.convert_class_logits_to_softmax)
self.assertEqual(args, {'temperature': 2})
