本文整理汇总了Python中object_detection.core.preprocessor.random_rotation90方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.random_rotation90方法的具体用法？Python preprocessor.random_rotation90怎么用？Python preprocessor.random_rotation90使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类object_detection.core.preprocessor的用法示例。
在下文中一共展示了preprocessor.random_rotation90方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: testRandomRotation90WithEmptyBoxes
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_rotation90 [as 别名]
def testRandomRotation90WithEmptyBoxes(self):
preprocess_options = [(preprocessor.random_rotation90, {})]
images = self.expectedImagesAfterNormalization()
boxes = self.createEmptyTestBoxes()
tensor_dict = {fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes}
images_expected1 = self.expectedImagesAfterRot90()
boxes_expected = self.createEmptyTestBoxes()
images_expected2 = images
tensor_dict = preprocessor.preprocess(tensor_dict, preprocess_options)
images = tensor_dict[fields.InputDataFields.image]
boxes = tensor_dict[fields.InputDataFields.groundtruth_boxes]
images_diff1 = tf.squared_difference(images, images_expected1)
images_diff2 = tf.squared_difference(images, images_expected2)
images_diff = tf.multiply(images_diff1, images_diff2)
images_diff_expected = tf.zeros_like(images_diff)
with self.test_session() as sess:
(images_diff_, images_diff_expected_, boxes_,
boxes_expected_) = sess.run([images_diff, images_diff_expected, boxes,
boxes_expected])
self.assertAllClose(boxes_, boxes_expected_)
self.assertAllClose(images_diff_, images_diff_expected_) 示例2: test_build_random_rotation90
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_rotation90 [as 别名]
def test_build_random_rotation90(self):
preprocessor_text_proto = """
random_rotation90 {
keypoint_rot_permutation: 3
keypoint_rot_permutation: 0
keypoint_rot_permutation: 1
keypoint_rot_permutation: 2
probability: 0.5
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.random_rotation90)
self.assertEqual(args, {'keypoint_rot_permutation': (3, 0, 1, 2),
'probability': 0.5}) 示例3: testRandomRotation90
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_rotation90 [as 别名]
def testRandomRotation90(self):
preprocess_options = [(preprocessor.random_rotation90, {})]
images = self.expectedImagesAfterNormalization()
boxes = self.createTestBoxes()
tensor_dict = {fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes}
images_expected1 = self.expectedImagesAfterRot90()
boxes_expected1 = self.expectedBoxesAfterRot90()
images_expected2 = images
boxes_expected2 = boxes
tensor_dict = preprocessor.preprocess(tensor_dict, preprocess_options)
images = tensor_dict[fields.InputDataFields.image]
boxes = tensor_dict[fields.InputDataFields.groundtruth_boxes]
boxes_diff1 = tf.squared_difference(boxes, boxes_expected1)
boxes_diff2 = tf.squared_difference(boxes, boxes_expected2)
boxes_diff = tf.multiply(boxes_diff1, boxes_diff2)
boxes_diff_expected = tf.zeros_like(boxes_diff)
images_diff1 = tf.squared_difference(images, images_expected1)
images_diff2 = tf.squared_difference(images, images_expected2)
images_diff = tf.multiply(images_diff1, images_diff2)
images_diff_expected = tf.zeros_like(images_diff)
with self.test_session() as sess:
(images_diff_, images_diff_expected_, boxes_diff_,
boxes_diff_expected_) = sess.run([images_diff, images_diff_expected,
boxes_diff, boxes_diff_expected])
self.assertAllClose(boxes_diff_, boxes_diff_expected_)
self.assertAllClose(images_diff_, images_diff_expected_) 示例4: testRandomRotation90WithCache
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_rotation90 [as 别名]
def testRandomRotation90WithCache(self):
preprocess_options = [(preprocessor.random_rotation90, {})]
self._testPreprocessorCache(preprocess_options,
test_boxes=True,
test_masks=True,
test_keypoints=True) 示例5: testRunRandomRotation90WithMaskAndKeypoints
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_rotation90 [as 别名]
def testRunRandomRotation90WithMaskAndKeypoints(self):
preprocess_options = [(preprocessor.random_rotation90, {})]
image_height = 3
image_width = 3
images = tf.random_uniform([1, image_height, image_width, 3])
boxes = self.createTestBoxes()
masks = self.createTestMasks()
keypoints = self.createTestKeypoints()
tensor_dict = {
fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_instance_masks: masks,
fields.InputDataFields.groundtruth_keypoints: keypoints
}
preprocessor_arg_map = preprocessor.get_default_func_arg_map(
include_instance_masks=True, include_keypoints=True)
tensor_dict = preprocessor.preprocess(
tensor_dict, preprocess_options, func_arg_map=preprocessor_arg_map)
boxes = tensor_dict[fields.InputDataFields.groundtruth_boxes]
masks = tensor_dict[fields.InputDataFields.groundtruth_instance_masks]
keypoints = tensor_dict[fields.InputDataFields.groundtruth_keypoints]
with self.test_session() as sess:
boxes, masks, keypoints = sess.run([boxes, masks, keypoints])
self.assertTrue(boxes is not None)
self.assertTrue(masks is not None)
self.assertTrue(keypoints is not None) 示例6: test_build_random_rotation90
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_rotation90 [as 别名]
def test_build_random_rotation90(self):
preprocessor_text_proto = """
random_rotation90 {}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.random_rotation90)
self.assertEqual(args, {})