本文整理汇总了Python中object_detection.core.preprocessor.random_resize_method方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.random_resize_method方法的具体用法？Python preprocessor.random_resize_method怎么用？Python preprocessor.random_resize_method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_resize_method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: testRandomResizeMethod
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_resize_method [as 别名]
def testRandomResizeMethod(self):
preprocessing_options = []
preprocessing_options.append((preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}))
preprocessing_options.append((preprocessor.random_resize_method, {
'target_size': (75, 150)
}))
images = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images}
resized_tensor_dict = preprocessor.preprocess(tensor_dict,
preprocessing_options)
resized_images = resized_tensor_dict[fields.InputDataFields.image]
resized_images_shape = tf.shape(resized_images)
expected_images_shape = tf.constant([1, 75, 150, 3], dtype=tf.int32)
with self.test_session() as sess:
(expected_images_shape_, resized_images_shape_) = sess.run(
[expected_images_shape, resized_images_shape])
self.assertAllEqual(expected_images_shape_,
resized_images_shape_) 示例2: testRandomResizeMethod
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_resize_method [as 别名]
def testRandomResizeMethod(self):
def graph_fn():
preprocessing_options = []
preprocessing_options.append((preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}))
preprocessing_options.append((preprocessor.random_resize_method, {
'target_size': (75, 150)
}))
images = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images}
resized_tensor_dict = preprocessor.preprocess(tensor_dict,
preprocessing_options)
resized_images = resized_tensor_dict[fields.InputDataFields.image]
resized_images_shape = tf.shape(resized_images)
expected_images_shape = tf.constant([1, 75, 150, 3], dtype=tf.int32)
return [expected_images_shape, resized_images_shape]
(expected_images_shape_, resized_images_shape_) = self.execute_cpu(graph_fn,
[])
self.assertAllEqual(expected_images_shape_,
resized_images_shape_) 示例3: test_build_random_resize_method
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_resize_method [as 别名]
def test_build_random_resize_method(self):
preprocessor_text_proto = """
random_resize_method {
target_height: 75
target_width: 100
}
"""
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_resize_method)
self.assert_dictionary_close(args, {'target_size': [75, 100]})