Python object_detection.core.post_processing.multiclass_non_max_suppression() Examples

The following are 30 code examples of object_detection.core.post_processing.multiclass_non_max_suppression(). 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.post_processing , or try the search function .
Example #1
Source File: post_processing_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #2
Source File: post_processing_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #3
Source File: post_processing_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #4
Source File: post_processing_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #5
Source File: post_processing_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #6
Source File: post_processing_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #7
Source File: post_processing_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #8
Source File: post_processing_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #9
Source File: post_processing_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #10
Source File: post_processing_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #11
Source File: post_processing_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #12
Source File: post_processing_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #13
Source File: post_processing_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #14
Source File: post_processing_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #15
Source File: post_processing_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #16
Source File: post_processing_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #17
Source File: post_processing_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #18
Source File: post_processing_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #19
Source File: post_processing_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms, _ = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #20
Source File: post_processing_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #21
Source File: post_processing_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #22
Source File: post_processing_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #23
Source File: post_processing_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #24
Source File: post_processing_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #25
Source File: post_processing_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #26
Source File: post_processing_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[0, 0, 1, 1]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window, change_coordinate_frame=True)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)
Example #27
Source File: post_processing_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]],
                         [[0, 1000, 1, 1002]],
                         [[0, 1000, 1, 1002.1]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
    score_thresh = 0.1
    iou_thresh = .5
    max_output_size = 3

    exp_nms = [[0, 10, 1, 11],
               [0, 0, 1, 1],
               [0, 100, 1, 101]]
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      nms_output = sess.run(nms.get())
      self.assertAllClose(nms_output, exp_nms)
Example #28
Source File: post_processing_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #29
Source File: post_processing_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_with_invalid_scores_size(self):
    boxes = tf.constant([[[0, 0, 1, 1]],
                         [[0, 0.1, 1, 1.1]],
                         [[0, -0.1, 1, 0.9]],
                         [[0, 10, 1, 11]],
                         [[0, 10.1, 1, 11.1]],
                         [[0, 100, 1, 101]]], tf.float32)
    scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
    iou_thresh = .5
    score_thresh = 0.6
    max_output_size = 3
    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size)
    with self.test_session() as sess:
      with self.assertRaisesWithPredicateMatch(
          tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
        sess.run(nms.get())
Example #30
Source File: post_processing_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_multiclass_nms_select_with_clip_window(self):
    boxes = tf.constant([[[0, 0, 10, 10]],
                         [[1, 1, 11, 11]]], tf.float32)
    scores = tf.constant([[.9], [.75]])
    clip_window = tf.constant([5, 4, 8, 7], tf.float32)
    score_thresh = 0.0
    iou_thresh = 0.5
    max_output_size = 100

    exp_nms_corners = [[5, 4, 8, 7]]
    exp_nms_scores = [.9]
    exp_nms_classes = [0]

    nms = post_processing.multiclass_non_max_suppression(
        boxes, scores, score_thresh, iou_thresh, max_output_size,
        clip_window=clip_window)
    with self.test_session() as sess:
      nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
          [nms.get(), nms.get_field(fields.BoxListFields.scores),
           nms.get_field(fields.BoxListFields.classes)])
      self.assertAllClose(nms_corners_output, exp_nms_corners)
      self.assertAllClose(nms_scores_output, exp_nms_scores)
      self.assertAllClose(nms_classes_output, exp_nms_classes)