Python preprocessor.random_crop_image方法代碼示例

本文整理匯總了Python中object_detection.core.preprocessor.random_crop_image方法的典型用法代碼示例。如果您正苦於以下問題：Python preprocessor.random_crop_image方法的具體用法？Python preprocessor.random_crop_image怎麽用？Python preprocessor.random_crop_image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.random_crop_image方法的12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: test_build_random_crop_image

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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,
    })

開發者ID:ringringyi，項目名稱:DOTA_models，代碼行數:25，代碼來源:preprocessor_builder_test.py

示例2: test_build_random_crop_image

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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,
    })

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:27，代碼來源:preprocessor_builder_test.py

示例3: testRandomCropImage

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:ringringyi，項目名稱:DOTA_models，代碼行數:35，代碼來源:preprocessor_test.py

示例4: testRandomCropImageGrayscale

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:ringringyi，項目名稱:DOTA_models，代碼行數:38，代碼來源:preprocessor_test.py

示例5: testRandomCropImageWithBoxOutOfImage

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:ringringyi，項目名稱:DOTA_models，代碼行數:34，代碼來源:preprocessor_test.py

示例6: testRandomCropImage

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:39，代碼來源:preprocessor_test.py

示例7: testRandomCropImageWithCache

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:16，代碼來源:preprocessor_test.py

示例8: testRandomCropImageGrayscale

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:40，代碼來源:preprocessor_test.py

示例9: testRandomCropImageWithBoxOutOfImage

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:38，代碼來源:preprocessor_test.py

示例10: testRandomCropImage

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:37，代碼來源:preprocessor_test.py

示例11: testRandomCropImageGrayscale

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:38，代碼來源:preprocessor_test.py

示例12: testRandomCropImageWithBoxOutOfImage

# 需要導入模塊: from object_detection.core import preprocessor [as 別名]
# 或者: from object_detection.core.preprocessor import random_crop_image [as 別名]
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_)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:36，代碼來源:preprocessor_test.py

注：本文中的object_detection.core.preprocessor.random_crop_image方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。