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Python preprocessor.random_image_scale方法代碼示例

本文整理匯總了Python中object_detection.core.preprocessor.random_image_scale方法的典型用法代碼示例。如果您正苦於以下問題:Python preprocessor.random_image_scale方法的具體用法?Python preprocessor.random_image_scale怎麽用?Python preprocessor.random_image_scale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: testRandomImageScale

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_image_scale [as 別名]
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]) 
開發者ID:ringringyi,項目名稱:DOTA_models,代碼行數:21,代碼來源:preprocessor_test.py

示例2: testRandomImageScale

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_image_scale [as 別名]
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]) 
開發者ID:tensorflow,項目名稱:models,代碼行數:24,代碼來源:preprocessor_test.py

示例3: test_build_random_image_scale

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_image_scale [as 別名]
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}) 
開發者ID:ringringyi,項目名稱:DOTA_models,代碼行數:15,代碼來源:preprocessor_builder_test.py


注:本文中的object_detection.core.preprocessor.random_image_scale方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台,相關代碼片段篩選自各路編程大神貢獻的開源項目,源碼版權歸原作者所有,傳播和使用請參考對應項目的License;未經允許,請勿轉載。