本文整理汇总了Python中object_detection.core.preprocessor.ssd_random_crop_pad方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.ssd_random_crop_pad方法的具体用法？Python preprocessor.ssd_random_crop_pad怎么用？Python preprocessor.ssd_random_crop_pad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.ssd_random_crop_pad方法的5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: testSSDRandomCropPad
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_pad [as 别名]
def testSSDRandomCropPad(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_pad, {})]
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: testSSDRandomCropPad
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_pad [as 别名]
def testSSDRandomCropPad(self):
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
weights = self.createTestGroundtruthWeights()
preprocessing_options = [
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}),
(preprocessor.ssd_random_crop_pad, {})]
tensor_dict = {
fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels,
fields.InputDataFields.groundtruth_weights: weights,
}
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3: testSSDRandomCropPad
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_pad [as 别名]
def testSSDRandomCropPad(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_pad, {})]
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4: testSSDRandomCropPad
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_pad [as 别名]
def testSSDRandomCropPad(self):
def graph_fn():
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
weights = self.createTestGroundtruthWeights()
preprocessing_options = [
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1
}),
(preprocessor.ssd_random_crop_pad, {})]
tensor_dict = {
fields.InputDataFields.image: images,
fields.InputDataFields.groundtruth_boxes: boxes,
fields.InputDataFields.groundtruth_classes: labels,
fields.InputDataFields.groundtruth_weights: weights,
}
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)
return [
boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
]
(boxes_rank_, distorted_boxes_rank_, images_rank_,
distorted_images_rank_) = self.execute_cpu(graph_fn, [])
self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
self.assertAllEqual(images_rank_, distorted_images_rank_) 示例5: test_build_ssd_random_crop_pad
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import ssd_random_crop_pad [as 别名]
def test_build_ssd_random_crop_pad(self):
preprocessor_text_proto = """
ssd_random_crop_pad {
operations {
min_object_covered: 0.0
min_aspect_ratio: 0.875
max_aspect_ratio: 1.125
min_area: 0.5
max_area: 1.0
overlap_thresh: 0.0
random_coef: 0.375
min_padded_size_ratio: [0.0, 0.0]
max_padded_size_ratio: [2.0, 2.0]
pad_color_r: 0.5
pad_color_g: 0.5
pad_color_b: 0.5
}
operations {
min_object_covered: 0.25
min_aspect_ratio: 0.75
max_aspect_ratio: 1.5
min_area: 0.5
max_area: 1.0
overlap_thresh: 0.25
random_coef: 0.375
min_padded_size_ratio: [0.0, 0.0]
max_padded_size_ratio: [2.0, 2.0]
pad_color_r: 0.5
pad_color_g: 0.5
pad_color_b: 0.5
}
}
"""
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_pad)
self.assertEqual(args, {'min_object_covered': [0.0, 0.25],
'aspect_ratio_range': [(0.875, 1.125), (0.75, 1.5)],
'area_range': [(0.5, 1.0), (0.5, 1.0)],
'overlap_thresh': [0.0, 0.25],
'random_coef': [0.375, 0.375],
'min_padded_size_ratio': [(0.0, 0.0), (0.0, 0.0)],
'max_padded_size_ratio': [(2.0, 2.0), (2.0, 2.0)],
'pad_color': [(0.5, 0.5, 0.5), (0.5, 0.5, 0.5)]})