Python object_detection.core.preprocessor.ssd_random_crop_pad() Examples

The following are 30 code examples of object_detection.core.preprocessor.ssd_random_crop_pad(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module object_detection.core.preprocessor , or try the search function .
Example #1
Source File: preprocessor_test.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
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_)
Example #2
Source File: preprocessor_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
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_)
Example #3
Source File: preprocessor_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
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_)
Example #4
Source File: preprocessor_test.py    From Accident-Detection-on-Indian-Roads with GNU Affero General Public License v3.0 5 votes vote down vote up 
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_)
Example #5
Source File: preprocessor_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
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_)
Example #6
Source File: preprocessor_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
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_)
Example #7
Source File: preprocessor_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
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_)
Example #8
Source File: preprocessor_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
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_)
Example #9
Source File: preprocessor_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
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_)
Example #10
Source File: preprocessor_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
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_)
Example #11
Source File: preprocessor_test.py    From hands-detection with MIT License 5 votes vote down vote up 
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_)
Example #12
Source File: preprocessor_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
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_)
Example #13
Source File: preprocessor_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
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_)
Example #14
Source File: preprocessor_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
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_)
Example #15
Source File: preprocessor_test.py    From MBMD with MIT License 5 votes vote down vote up 
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_)
Example #16
Source File: preprocessor_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
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_)
Example #17
Source File: preprocessor_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
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_)
Example #18
Source File: preprocessor_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
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_)
Example #19
Source File: preprocessor_test.py    From models with Apache License 2.0 5 votes vote down vote up 
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_)
Example #20
Source File: preprocessor_test.py    From yolo_v2 with Apache License 2.0 5 votes vote down vote up 
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_)
Example #21
Source File: preprocessor_test.py    From object_detector_app with MIT License 5 votes vote down vote up 
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_)
Example #22
Source File: preprocessor_test.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
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_)
Example #23
Source File: preprocessor_test.py    From HereIsWally with MIT License 5 votes vote down vote up 
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_)
Example #24
Source File: preprocessor_test.py    From motion-rcnn with MIT License 5 votes vote down vote up 
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_)
Example #25
Source File: preprocessor_test.py    From garbage-object-detection-tensorflow with MIT License 5 votes vote down vote up 
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_)
Example #26
Source File: preprocessor_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
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_)
Example #27
Source File: preprocessor_test.py    From Person-Detection-and-Tracking with MIT License 5 votes vote down vote up 
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_)
Example #28
Source File: preprocessor_test.py    From mtl-ssl with Apache License 2.0 5 votes vote down vote up 
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_)
Example #29
Source File: preprocessor_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
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_)
Example #30
Source File: preprocessor_builder_test.py    From multilabel-image-classification-tensorflow with MIT License 4 votes vote down vote up 
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
        clip_boxes: False
        random_coef: 0.375
        min_padded_size_ratio: [1.0, 1.0]
        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
        clip_boxes: True
        random_coef: 0.375
        min_padded_size_ratio: [1.0, 1.0]
        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],
                            'clip_boxes': [False, True],
                            'random_coef': [0.375, 0.375],
                            'min_padded_size_ratio': [(1.0, 1.0), (1.0, 1.0)],
                            '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)]})