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Python preprocessor.random_crop_image方法代码示例

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, 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,
    }) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:25,代码来源:preprocessor_builder_test.py

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,
    }) 
开发者ID:ahmetozlu,项目名称:vehicle_counting_tensorflow,代码行数:27,代码来源:preprocessor_builder_test.py

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_) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:35,代码来源:preprocessor_test.py

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_) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:38,代码来源:preprocessor_test.py

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_) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:34,代码来源:preprocessor_test.py

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_) 
开发者ID:ahmetozlu,项目名称:vehicle_counting_tensorflow,代码行数:39,代码来源:preprocessor_test.py

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) 
开发者ID:ahmetozlu,项目名称:vehicle_counting_tensorflow,代码行数:16,代码来源:preprocessor_test.py

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_) 
开发者ID:ahmetozlu,项目名称:vehicle_counting_tensorflow,代码行数:40,代码来源:preprocessor_test.py

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_) 
开发者ID:ahmetozlu,项目名称:vehicle_counting_tensorflow,代码行数:38,代码来源:preprocessor_test.py

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_) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:37,代码来源:preprocessor_test.py

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_) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:38,代码来源:preprocessor_test.py

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_) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:36,代码来源:preprocessor_test.py


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