Python object_detection.utils.visualization_utils.add_hist_image_summary() Examples
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Example #1
Source File: visualization_utils_test.py From vehicle_counting_tensorflow with MIT License | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #2
Source File: visualization_utils_test.py From Person-Detection-and-Tracking with MIT License | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #3
Source File: visualization_utils_test.py From Gun-Detector with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #4
Source File: visualization_utils_test.py From ros_tensorflow with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #5
Source File: visualization_utils_test.py From BMW-TensorFlow-Training-GUI with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #6
Source File: visualization_utils_test.py From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #7
Source File: visualization_utils_test.py From MAX-Object-Detector with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #8
Source File: visualization_utils_test.py From g-tensorflow-models with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()
Example #9
Source File: visualization_utils_test.py From models with Apache License 2.0 | 5 votes |
def test_add_hist_image_summary(self): def graph_fn(): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] return hist_image_summary self.execute(graph_fn, [])
Example #10
Source File: visualization_utils_test.py From multilabel-image-classification-tensorflow with MIT License | 5 votes |
def test_add_hist_image_summary(self): values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50] bins = [0.01 * i for i in range(101)] visualization_utils.add_hist_image_summary(values, bins, 'ScoresDistribution') hist_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0] with self.test_session(): hist_image_summary.eval()