本文整理汇总了Python中object_detection.core.preprocessor.random_adjust_brightness方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.random_adjust_brightness方法的具体用法？Python preprocessor.random_adjust_brightness怎么用？Python preprocessor.random_adjust_brightness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_adjust_brightness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: testRandomAdjustBrightness
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_adjust_brightness [as 别名]
def testRandomAdjustBrightness(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_adjust_brightness, {}))
images_original = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images_original}
tensor_dict = preprocessor.preprocess(tensor_dict, preprocessing_options)
images_bright = tensor_dict[fields.InputDataFields.image]
image_original_shape = tf.shape(images_original)
image_bright_shape = tf.shape(images_bright)
with self.test_session() as sess:
(image_original_shape_, image_bright_shape_) = sess.run(
[image_original_shape, image_bright_shape])
self.assertAllEqual(image_original_shape_, image_bright_shape_) 示例2: testRandomAdjustBrightness
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_adjust_brightness [as 别名]
def testRandomAdjustBrightness(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_adjust_brightness, {}))
images_original = self.createTestImages()
tensor_dict = {fields.InputDataFields.image: images_original}
tensor_dict = preprocessor.preprocess(tensor_dict, preprocessing_options)
images_bright = tensor_dict[fields.InputDataFields.image]
image_original_shape = tf.shape(images_original)
image_bright_shape = tf.shape(images_bright)
return [image_original_shape, image_bright_shape]
(image_original_shape_,
image_bright_shape_) = self.execute_cpu(graph_fn, [])
self.assertAllEqual(image_original_shape_, image_bright_shape_) 示例3: test_build_random_adjust_brightness
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_adjust_brightness [as 别名]
def test_build_random_adjust_brightness(self):
preprocessor_text_proto = """
random_adjust_brightness {
max_delta: 0.2
}
"""
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_adjust_brightness)
self.assert_dictionary_close(args, {'max_delta': 0.2})