本文整理汇总了Python中object_detection.core.preprocessor.random_crop_image方法的典型用法代码示例。如果您正苦于以下问题：Python preprocessor.random_crop_image方法的具体用法？Python preprocessor.random_crop_image怎么用？Python preprocessor.random_crop_image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_crop_image方法的12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: test_build_random_crop_image
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def test_build_random_crop_image(self):
preprocessor_text_proto = """
random_crop_image {
min_object_covered: 0.75
min_aspect_ratio: 0.75
max_aspect_ratio: 1.5
min_area: 0.25
max_area: 0.875
overlap_thresh: 0.5
random_coef: 0.125
}
"""
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_crop_image)
self.assertEqual(args, {
'min_object_covered': 0.75,
'aspect_ratio_range': (0.75, 1.5),
'area_range': (0.25, 0.875),
'overlap_thresh': 0.5,
'random_coef': 0.125,
}) 示例2: test_build_random_crop_image
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def test_build_random_crop_image(self):
preprocessor_text_proto = """
random_crop_image {
min_object_covered: 0.75
min_aspect_ratio: 0.75
max_aspect_ratio: 1.5
min_area: 0.25
max_area: 0.875
overlap_thresh: 0.5
clip_boxes: False
random_coef: 0.125
}
"""
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_crop_image)
self.assertEqual(args, {
'min_object_covered': 0.75,
'aspect_ratio_range': (0.75, 1.5),
'area_range': (0.25, 0.875),
'overlap_thresh': 0.5,
'clip_boxes': False,
'random_coef': 0.125,
}) 示例3: testRandomCropImage
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImage(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_crop_image, {}))
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}
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
self.assertEqual(3, distorted_images.get_shape()[3])
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: testRandomCropImageGrayscale
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageGrayscale(self):
preprocessing_options = [(preprocessor.rgb_to_gray, {}),
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1,
}),
(preprocessor.random_crop_image, {})]
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
}
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
self.assertEqual(1, distorted_images.get_shape()[3])
with self.test_session() as sess:
session_results = sess.run([
boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
])
(boxes_rank_, distorted_boxes_rank_, images_rank_,
distorted_images_rank_) = session_results
self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
self.assertAllEqual(images_rank_, distorted_images_rank_) 示例5: testRandomCropImageWithBoxOutOfImage
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageWithBoxOutOfImage(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_crop_image, {}))
images = self.createTestImages()
boxes = self.createTestBoxesOutOfImage()
labels = self.createTestLabels()
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
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6: testRandomCropImage
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImage(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_crop_image, {}))
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
weights = self.createTestGroundtruthWeights()
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
self.assertEqual(3, distorted_images.get_shape()[3])
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7: testRandomCropImageWithCache
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageWithCache(self):
preprocess_options = [(preprocessor.random_rgb_to_gray,
{'probability': 0.5}),
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1,
}),
(preprocessor.random_crop_image, {})]
self._testPreprocessorCache(preprocess_options,
test_boxes=True,
test_masks=False,
test_keypoints=False) 示例8: testRandomCropImageGrayscale
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageGrayscale(self):
preprocessing_options = [(preprocessor.rgb_to_gray, {}),
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1,
}),
(preprocessor.random_crop_image, {})]
images = self.createTestImages()
boxes = self.createTestBoxes()
labels = self.createTestLabels()
weights = self.createTestGroundtruthWeights()
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
self.assertEqual(1, distorted_images.get_shape()[3])
with self.test_session() as sess:
session_results = sess.run([
boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
])
(boxes_rank_, distorted_boxes_rank_, images_rank_,
distorted_images_rank_) = session_results
self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
self.assertAllEqual(images_rank_, distorted_images_rank_) 示例9: testRandomCropImageWithBoxOutOfImage
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageWithBoxOutOfImage(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_crop_image, {}))
images = self.createTestImages()
boxes = self.createTestBoxesOutOfImage()
labels = self.createTestLabels()
weights = self.createTestGroundtruthWeights()
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
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10: testRandomCropImage
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImage(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_crop_image, {}))
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,
}
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
self.assertEqual(3, distorted_images.get_shape()[3])
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11: testRandomCropImageGrayscale
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageGrayscale(self):
preprocessing_options = [(preprocessor.rgb_to_gray, {}),
(preprocessor.normalize_image, {
'original_minval': 0,
'original_maxval': 255,
'target_minval': 0,
'target_maxval': 1,
}),
(preprocessor.random_crop_image, {})]
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,
}
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
self.assertEqual(1, distorted_images.get_shape()[3])
with self.test_session() as sess:
session_results = sess.run([
boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
])
(boxes_rank_, distorted_boxes_rank_, images_rank_,
distorted_images_rank_) = session_results
self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
self.assertAllEqual(images_rank_, distorted_images_rank_) 示例12: testRandomCropImageWithBoxOutOfImage
# 需要导入模块: from object_detection.core import preprocessor [as 别名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 别名]
def testRandomCropImageWithBoxOutOfImage(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_crop_image, {}))
images = self.createTestImages()
boxes = self.createTestBoxesOutOfImage()
labels = self.createTestLabels()
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]
boxes_rank = tf.rank(boxes)
distorted_boxes_rank = tf.rank(distorted_boxes)
images_rank = tf.rank(images)
distorted_images_rank = tf.rank(distorted_images)
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_)