本文整理汇总了Python中object_detection.core.preprocessor.random_pad_to_aspect_ratio方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.random_pad_to_aspect_ratio方法的具体用法？Python preprocessor.random_pad_to_aspect_ratio怎么用？Python preprocessor.random_pad_to_aspect_ratio使用的例子？那么, 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_pad_to_aspect_ratio方法的4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: testRandomPadToAspectRatioWithCache
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_pad_to_aspect_ratio [as 别名]
def testRandomPadToAspectRatioWithCache(self):
preprocess_options = [(preprocessor.random_pad_to_aspect_ratio, {})]
self._testPreprocessorCache(preprocess_options,
test_boxes=True,
test_masks=True,
test_keypoints=True) 示例2: testRunRandomPadToAspectRatioWithMinMaxPaddedSizeRatios
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_pad_to_aspect_ratio [as 别名]
def testRunRandomPadToAspectRatioWithMinMaxPaddedSizeRatios(self):
image = self.createColorfulTestImage()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
tensor_dict = {
fields.InputDataFields.image: image,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels
}
preprocessor_arg_map = preprocessor.get_default_func_arg_map()
preprocessing_options = [(preprocessor.random_pad_to_aspect_ratio,
{'min_padded_size_ratio': (4.0, 4.0),
'max_padded_size_ratio': (4.0, 4.0)})]
distorted_tensor_dict = preprocessor.preprocess(
tensor_dict, preprocessing_options, func_arg_map=preprocessor_arg_map)
distorted_image = distorted_tensor_dict[fields.InputDataFields.image]
distorted_boxes = distorted_tensor_dict[
fields.InputDataFields.groundtruth_boxes]
distorted_labels = distorted_tensor_dict[
fields.InputDataFields.groundtruth_classes]
with self.test_session() as sess:
distorted_image_, distorted_boxes_, distorted_labels_ = sess.run([
distorted_image, distorted_boxes, distorted_labels])
expected_boxes = np.array(
[[0.0, 0.125, 0.1875, 0.5], [0.0625, 0.25, 0.1875, 0.5]],
dtype=np.float32)
self.assertAllEqual(distorted_image_.shape, [1, 800, 800, 3])
self.assertAllEqual(distorted_labels_, [1, 2])
self.assertAllClose(distorted_boxes_.flatten(),
expected_boxes.flatten()) 示例3: testRunRandomPadToAspectRatioWithMasks
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_pad_to_aspect_ratio [as 别名]
def testRunRandomPadToAspectRatioWithMasks(self):
image = self.createColorfulTestImage()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
masks = tf.random_uniform([2, 200, 400], dtype=tf.float32)
tensor_dict = {
fields.InputDataFields.image: image,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels,
fields.InputDataFields.groundtruth_instance_masks: masks
}
preprocessor_arg_map = preprocessor.get_default_func_arg_map(
include_instance_masks=True)
preprocessing_options = [(preprocessor.random_pad_to_aspect_ratio, {})]
distorted_tensor_dict = preprocessor.preprocess(
tensor_dict, preprocessing_options, func_arg_map=preprocessor_arg_map)
distorted_image = distorted_tensor_dict[fields.InputDataFields.image]
distorted_boxes = distorted_tensor_dict[
fields.InputDataFields.groundtruth_boxes]
distorted_labels = distorted_tensor_dict[
fields.InputDataFields.groundtruth_classes]
distorted_masks = distorted_tensor_dict[
fields.InputDataFields.groundtruth_instance_masks]
with self.test_session() as sess:
(distorted_image_, distorted_boxes_, distorted_labels_,
distorted_masks_) = sess.run([
distorted_image, distorted_boxes, distorted_labels, distorted_masks
])
expected_boxes = np.array(
[[0.0, 0.25, 0.375, 1.0], [0.125, 0.5, 0.375, 1.0]], dtype=np.float32)
self.assertAllEqual(distorted_image_.shape, [1, 400, 400, 3])
self.assertAllEqual(distorted_labels_, [1, 2])
self.assertAllClose(distorted_boxes_.flatten(),
expected_boxes.flatten())
self.assertAllEqual(distorted_masks_.shape, [2, 400, 400]) 示例4: testRandomPadToAspectRatio
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_pad_to_aspect_ratio [as 别名]
def testRandomPadToAspectRatio(self):
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
tensor_dict = {
fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels,
}
tensor_dict = preprocessor.preprocess(tensor_dict, [])
images = tensor_dict[fields.InputDataFields.image]
preprocessing_options = [(preprocessor.random_pad_to_aspect_ratio, {
'aspect_ratio': 2.0
})]
padded_tensor_dict = preprocessor.preprocess(tensor_dict,
preprocessing_options)
padded_images = padded_tensor_dict[fields.InputDataFields.image]
padded_boxes = padded_tensor_dict[
fields.InputDataFields.groundtruth_boxes]
boxes_shape = tf.shape(boxes)
padded_boxes_shape = tf.shape(padded_boxes)
images_shape = tf.shape(images)
padded_images_shape = tf.shape(padded_images)
with self.test_session() as sess:
(boxes_shape_, padded_boxes_shape_, images_shape_,
padded_images_shape_) = sess.run([
boxes_shape, padded_boxes_shape, images_shape, padded_images_shape
])
self.assertAllEqual(boxes_shape_, padded_boxes_shape_)
self.assertEqual(images_shape_[1], padded_images_shape_[1])
self.assertEqual(2 * images_shape_[2], padded_images_shape_[2])