本文整理匯總了Python中object_detection.core.preprocessor.ssd_random_crop_fixed_aspect_ratio方法的典型用法代碼示例。如果您正苦於以下問題：Python preprocessor.ssd_random_crop_fixed_aspect_ratio方法的具體用法？Python preprocessor.ssd_random_crop_fixed_aspect_ratio怎麽用？Python preprocessor.ssd_random_crop_fixed_aspect_ratio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類object_detection.core.preprocessor的用法示例。
在下文中一共展示了preprocessor.ssd_random_crop_fixed_aspect_ratio方法的5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: testSSDRandomCropFixedAspectRatio
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_fixed_aspect_ratio [as 別名]
def testSSDRandomCropFixedAspectRatio(self):
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
preprocessing_options = [
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}),
(preprocessor.ssd_random_crop_fixed_aspect_ratio, {})]
tensor_dict = {
fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels
}
distorted_tensor_dict = preprocessor.preprocess(tensor_dict,
preprocessing_options)
distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
distorted_boxes = distorted_tensor_dict[
fields.InputDataFields.groundtruth_boxes]
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
with self.test_session() as sess:
(boxes_rank_, distorted_boxes_rank_, images_rank_,
distorted_images_rank_) = sess.run(
[boxes_rank, distorted_boxes_rank, images_rank,
distorted_images_rank])
self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
self.assertAllEqual(images_rank_, distorted_images_rank_) 示例2: testSSDRandomCropFixedAspectRatioWithMasksAndKeypoints
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_fixed_aspect_ratio [as 別名]
def testSSDRandomCropFixedAspectRatioWithMasksAndKeypoints(self):
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
masks = self.createTestMasks()
keypoints = self.createTestKeypoints()
preprocessing_options = [
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}),
(preprocessor.ssd_random_crop_fixed_aspect_ratio, {})]
tensor_dict = {
fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels,
fields.InputDataFields.groundtruth_instance_masks: masks,
fields.InputDataFields.groundtruth_keypoints: keypoints,
}
preprocessor_arg_map = preprocessor.get_default_func_arg_map(
include_instance_masks=True, include_keypoints=True)
distorted_tensor_dict = preprocessor.preprocess(
tensor_dict, preprocessing_options, func_arg_map=preprocessor_arg_map)
distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
distorted_boxes = distorted_tensor_dict[
fields.InputDataFields.groundtruth_boxes]
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
with self.test_session() as sess:
(boxes_rank_, distorted_boxes_rank_, images_rank_,
distorted_images_rank_) = sess.run(
[boxes_rank, distorted_boxes_rank, images_rank,
distorted_images_rank])
self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
self.assertAllEqual(images_rank_, distorted_images_rank_) 示例3: test_build_ssd_random_crop_fixed_aspect_ratio
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_fixed_aspect_ratio [as 別名]
def test_build_ssd_random_crop_fixed_aspect_ratio(self):
preprocessor_text_proto = """
ssd_random_crop_fixed_aspect_ratio {
operations {
min_object_covered: 0.0
min_area: 0.5
max_area: 1.0
overlap_thresh: 0.0
random_coef: 0.375
}
operations {
min_object_covered: 0.25
min_area: 0.5
max_area: 1.0
overlap_thresh: 0.25
random_coef: 0.375
}
aspect_ratio: 0.875
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.ssd_random_crop_fixed_aspect_ratio)
self.assertEqual(args, {'min_object_covered': [0.0, 0.25],
'aspect_ratio': 0.875,
'area_range': [(0.5, 1.0), (0.5, 1.0)],
'overlap_thresh': [0.0, 0.25],
'random_coef': [0.375, 0.375]}) 示例4: testSSDRandomCropFixedAspectRatioWithCache
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_fixed_aspect_ratio [as 別名]
def testSSDRandomCropFixedAspectRatioWithCache(self):
preprocess_options = [
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}),
(preprocessor.ssd_random_crop_fixed_aspect_ratio, {})]
self._testPreprocessorCache(preprocess_options,
test_boxes=True,
test_masks=False,
test_keypoints=False) 示例5: test_build_ssd_random_crop_fixed_aspect_ratio
# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_fixed_aspect_ratio [as 別名]
def test_build_ssd_random_crop_fixed_aspect_ratio(self):
preprocessor_text_proto = """
ssd_random_crop_fixed_aspect_ratio {
operations {
min_object_covered: 0.0
min_area: 0.5
max_area: 1.0
overlap_thresh: 0.0
clip_boxes: False
random_coef: 0.375
}
operations {
min_object_covered: 0.25
min_area: 0.5
max_area: 1.0
overlap_thresh: 0.25
clip_boxes: True
random_coef: 0.375
}
aspect_ratio: 0.875
}
"""
preprocessor_proto = preprocessor_pb2.PreprocessingStep()
text_format.Merge(preprocessor_text_proto, preprocessor_proto)
function, args = preprocessor_builder.build(preprocessor_proto)
self.assertEqual(function, preprocessor.ssd_random_crop_fixed_aspect_ratio)
self.assertEqual(args, {'min_object_covered': [0.0, 0.25],
'aspect_ratio': 0.875,
'area_range': [(0.5, 1.0), (0.5, 1.0)],
'overlap_thresh': [0.0, 0.25],
'clip_boxes': [False, True],
'random_coef': [0.375, 0.375]})