本文整理汇总了Python中object_detection.core.preprocessor.random_image_scale方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.random_image_scale方法的具体用法？Python preprocessor.random_image_scale怎么用？Python preprocessor.random_image_scale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_image_scale方法的3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: testRandomImageScale
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_image_scale [as 别名]
def testRandomImageScale(self):
preprocess_options = [(preprocessor.random_image_scale, {})]
images_original = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images_original}
tensor_dict = preprocessor.preprocess(tensor_dict, preprocess_options)
images_scaled = tensor_dict[fields.InputDataFields.image]
images_original_shape = tf.shape(images_original)
images_scaled_shape = tf.shape(images_scaled)
with self.test_session() as sess:
(images_original_shape_, images_scaled_shape_) = sess.run(
[images_original_shape, images_scaled_shape])
self.assertTrue(
images_original_shape_[1] * 0.5 <= images_scaled_shape_[1])
self.assertTrue(
images_original_shape_[1] * 2.0 >= images_scaled_shape_[1])
self.assertTrue(
images_original_shape_[2] * 0.5 <= images_scaled_shape_[2])
self.assertTrue(
images_original_shape_[2] * 2.0 >= images_scaled_shape_[2]) 示例2: testRandomImageScale
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_image_scale [as 别名]
def testRandomImageScale(self):
def graph_fn():
preprocess_options = [(preprocessor.random_image_scale, {})]
images_original = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images_original}
tensor_dict = preprocessor.preprocess(tensor_dict, preprocess_options)
images_scaled = tensor_dict[fields.InputDataFields.image]
images_original_shape = tf.shape(images_original)
images_scaled_shape = tf.shape(images_scaled)
return [images_original_shape, images_scaled_shape]
(images_original_shape_,
images_scaled_shape_) = self.execute_cpu(graph_fn, [])
self.assertLessEqual(images_original_shape_[1] * 0.5,
images_scaled_shape_[1])
self.assertGreaterEqual(images_original_shape_[1] * 2.0,
images_scaled_shape_[1])
self.assertLessEqual(images_original_shape_[2] * 0.5,
images_scaled_shape_[2])
self.assertGreaterEqual(images_original_shape_[2] * 2.0,
images_scaled_shape_[2]) 示例3: test_build_random_image_scale
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_image_scale [as 别名]
def test_build_random_image_scale(self):
preprocessor_text_proto = """
random_image_scale {
min_scale_ratio: 0.8
max_scale_ratio: 2.2
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.random_image_scale)
self.assert_dictionary_close(args, {'min_scale_ratio': 0.8,
'max_scale_ratio': 2.2})