本文整理匯總了Python中object_detection.core.keypoint_ops.flip_horizontal方法的典型用法代碼示例。如果您正苦於以下問題：Python keypoint_ops.flip_horizontal方法的具體用法？Python keypoint_ops.flip_horizontal怎麽用？Python keypoint_ops.flip_horizontal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.core.keypoint_ops的用法示例。
在下文中一共展示了keypoint_ops.flip_horizontal方法的3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_flip_horizontal
# 需要導入模塊: from object_detection.core import keypoint_ops [as 別名]
# 或者: from object_detection.core.keypoint_ops import flip_horizontal [as 別名]
def test_flip_horizontal(self):
keypoints = tf.constant([
[[0.1, 0.1], [0.2, 0.2], [0.3, 0.3]],
[[0.4, 0.4], [0.5, 0.5], [0.6, 0.6]]
])
flip_permutation = [0, 2, 1]
expected_keypoints = tf.constant([
[[0.1, 0.9], [0.3, 0.7], [0.2, 0.8]],
[[0.4, 0.6], [0.6, 0.4], [0.5, 0.5]],
])
output = keypoint_ops.flip_horizontal(keypoints, 0.5, flip_permutation)
with self.test_session() as sess:
output_, expected_keypoints_ = sess.run([output, expected_keypoints])
self.assertAllClose(output_, expected_keypoints_) 示例2: test_flip_horizontal
# 需要導入模塊: from object_detection.core import keypoint_ops [as 別名]
# 或者: from object_detection.core.keypoint_ops import flip_horizontal [as 別名]
def test_flip_horizontal(self):
def graph_fn():
keypoints = tf.constant([
[[0.1, 0.1], [0.2, 0.2], [0.3, 0.3]],
[[0.4, 0.4], [0.5, 0.5], [0.6, 0.6]]
])
expected_keypoints = tf.constant([
[[0.1, 0.9], [0.2, 0.8], [0.3, 0.7]],
[[0.4, 0.6], [0.5, 0.5], [0.6, 0.4]],
])
output = keypoint_ops.flip_horizontal(keypoints, 0.5)
return output, expected_keypoints
output, expected_keypoints = self.execute(graph_fn, [])
self.assertAllClose(output, expected_keypoints) 示例3: test_flip_horizontal_permutation
# 需要導入模塊: from object_detection.core import keypoint_ops [as 別名]
# 或者: from object_detection.core.keypoint_ops import flip_horizontal [as 別名]
def test_flip_horizontal_permutation(self):
def graph_fn():
keypoints = tf.constant([[[0.1, 0.1], [0.2, 0.2], [0.3, 0.3]],
[[0.4, 0.4], [0.5, 0.5], [0.6, 0.6]]])
flip_permutation = [0, 2, 1]
expected_keypoints = tf.constant([
[[0.1, 0.9], [0.3, 0.7], [0.2, 0.8]],
[[0.4, 0.6], [0.6, 0.4], [0.5, 0.5]],
])
output = keypoint_ops.flip_horizontal(keypoints, 0.5, flip_permutation)
return output, expected_keypoints
output, expected_keypoints = self.execute(graph_fn, [])
self.assertAllClose(output, expected_keypoints)