本文整理匯總了Python中object_detection.utils.visualization_utils.add_cdf_image_summary方法的典型用法代碼示例。如果您正苦於以下問題：Python visualization_utils.add_cdf_image_summary方法的具體用法？Python visualization_utils.add_cdf_image_summary怎麽用？Python visualization_utils.add_cdf_image_summary使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類object_detection.utils.visualization_utils的用法示例。
在下文中一共展示了visualization_utils.add_cdf_image_summary方法的4個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_add_cdf_image_summary
# 需要導入模塊: from object_detection.utils import visualization_utils [as 別名]
# 或者: from object_detection.utils.visualization_utils import add_cdf_image_summary [as 別名]
def test_add_cdf_image_summary(self):
values = [0.1, 0.2, 0.3, 0.4, 0.42, 0.44, 0.46, 0.48, 0.50]
visualization_utils.add_cdf_image_summary(values, 'PositiveAnchorLoss')
cdf_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0]
with self.test_session():
cdf_image_summary.eval() 示例2: _summarize_anchor_classification_loss
# 需要導入模塊: from object_detection.utils import visualization_utils [as 別名]
# 或者: from object_detection.utils.visualization_utils import add_cdf_image_summary [as 別名]
def _summarize_anchor_classification_loss(self, class_ids, cls_losses):
positive_indices = tf.where(tf.greater(class_ids, 0))
positive_anchor_cls_loss = tf.squeeze(
tf.gather(cls_losses, positive_indices), axis=1)
visualization_utils.add_cdf_image_summary(positive_anchor_cls_loss,
'PositiveAnchorLossCDF')
negative_indices = tf.where(tf.equal(class_ids, 0))
negative_anchor_cls_loss = tf.squeeze(
tf.gather(cls_losses, negative_indices), axis=1)
visualization_utils.add_cdf_image_summary(negative_anchor_cls_loss,
'NegativeAnchorLossCDF') 示例3: _summarize_anchor_classification_loss
# 需要導入模塊: from object_detection.utils import visualization_utils [as 別名]
# 或者: from object_detection.utils.visualization_utils import add_cdf_image_summary [as 別名]
def _summarize_anchor_classification_loss(self, class_ids, cls_losses):
positive_indices = tf.where(tf.greater(class_ids, 0))
positive_anchor_cls_loss = tf.squeeze(
tf.gather(cls_losses, positive_indices), axis=1)
# visualization_utils.add_cdf_image_summary(positive_anchor_cls_loss,
# 'PositiveAnchorLossCDF')
negative_indices = tf.where(tf.equal(class_ids, 0))
negative_anchor_cls_loss = tf.squeeze(
tf.gather(cls_losses, negative_indices), axis=1)
# visualization_utils.add_cdf_image_summary(negative_anchor_cls_loss,
# 'NegativeAnchorLossCDF') 示例4: test_add_cdf_image_summary
# 需要導入模塊: from object_detection.utils import visualization_utils [as 別名]
# 或者: from object_detection.utils.visualization_utils import add_cdf_image_summary [as 別名]
def test_add_cdf_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]
visualization_utils.add_cdf_image_summary(values, 'PositiveAnchorLoss')
cdf_image_summary = tf.get_collection(key=tf.GraphKeys.SUMMARIES)[0]
return cdf_image_summary
self.execute(graph_fn, [])