Python np_box_mask_list_ops.ioa方法代码示例

本文整理汇总了Python中object_detection.utils.np_box_mask_list_ops.ioa方法的典型用法代码示例。如果您正苦于以下问题：Python np_box_mask_list_ops.ioa方法的具体用法？Python np_box_mask_list_ops.ioa怎么用？Python np_box_mask_list_ops.ioa使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类object_detection.utils.np_box_mask_list_ops的用法示例。

在下文中一共展示了np_box_mask_list_ops.ioa方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_ioa

# 需要导入模块: from object_detection.utils import np_box_mask_list_ops [as 别名]
# 或者: from object_detection.utils.np_box_mask_list_ops import ioa [as 别名]
def test_ioa(self):
    ioa21 = np_box_mask_list_ops.ioa(self.box_mask_list1, self.box_mask_list2)
    expected_ioa21 = np.array([[1.0, 0.0, 8.0/25.0],
                               [0.0, 9.0/15.0, 7.0/25.0]],
                              dtype=np.float32)
    self.assertAllClose(ioa21, expected_ioa21)

开发者ID:ahmetozlu，项目名称:vehicle_counting_tensorflow，代码行数:8，代码来源:np_box_mask_list_ops_test.py

示例2: _get_overlaps_and_scores_box_mode

# 需要导入模块: from object_detection.utils import np_box_mask_list_ops [as 别名]
# 或者: from object_detection.utils.np_box_mask_list_ops import ioa [as 别名]
def _get_overlaps_and_scores_box_mode(
      self,
      detected_boxes,
      detected_scores,
      groundtruth_boxes,
      groundtruth_is_group_of_list):
    """Computes overlaps and scores between detected and groudntruth boxes.

    Args:
      detected_boxes: A numpy array of shape [N, 4] representing detected box
          coordinates
      detected_scores: A 1-d numpy array of length N representing classification
          score
      groundtruth_boxes: A numpy array of shape [M, 4] representing ground truth
          box coordinates
      groundtruth_is_group_of_list: A boolean numpy array of length M denoting
          whether a ground truth box has group-of tag. If a groundtruth box
          is group-of box, every detection matching this box is ignored.

    Returns:
      iou: A float numpy array of size [num_detected_boxes, num_gt_boxes]. If
          gt_non_group_of_boxlist.num_boxes() == 0 it will be None.
      ioa: A float numpy array of size [num_detected_boxes, num_gt_boxes]. If
          gt_group_of_boxlist.num_boxes() == 0 it will be None.
      scores: The score of the detected boxlist.
      num_boxes: Number of non-maximum suppressed detected boxes.
    """
    detected_boxlist = np_box_list.BoxList(detected_boxes)
    detected_boxlist.add_field('scores', detected_scores)
    detected_boxlist = np_box_list_ops.non_max_suppression(
        detected_boxlist, self.nms_max_output_boxes, self.nms_iou_threshold)
    gt_non_group_of_boxlist = np_box_list.BoxList(
        groundtruth_boxes[~groundtruth_is_group_of_list])
    gt_group_of_boxlist = np_box_list.BoxList(
        groundtruth_boxes[groundtruth_is_group_of_list])
    iou = np_box_list_ops.iou(detected_boxlist, gt_non_group_of_boxlist)
    ioa = np.transpose(
        np_box_list_ops.ioa(gt_group_of_boxlist, detected_boxlist))
    scores = detected_boxlist.get_field('scores')
    num_boxes = detected_boxlist.num_boxes()
    return iou, ioa, scores, num_boxes

开发者ID:ahmetozlu，项目名称:vehicle_counting_tensorflow，代码行数:43，代码来源:per_image_evaluation.py

示例3: _get_overlaps_and_scores_box_mode

# 需要导入模块: from object_detection.utils import np_box_mask_list_ops [as 别名]
# 或者: from object_detection.utils.np_box_mask_list_ops import ioa [as 别名]
def _get_overlaps_and_scores_box_mode(
      self,
      detected_boxes,
      detected_scores,
      groundtruth_boxes,
      groundtruth_is_group_of_list):
    """Computes overlaps and scores between detected and groudntruth boxes.

    Args:
      detected_boxes: A numpy array of shape [N, 4] representing detected box
          coordinates
      detected_scores: A 1-d numpy array of length N representing classification
          score
      groundtruth_boxes: A numpy array of shape [M, 4] representing ground truth
          box coordinates
      groundtruth_is_group_of_list: A boolean numpy array of length M denoting
          whether a ground truth box has group-of tag. If a groundtruth box
          is group-of box, every detection matching this box is ignored.

    Returns:
      iou: A float numpy array of size [num_detected_boxes, num_gt_boxes]. If
          gt_non_group_of_boxlist.num_boxes() == 0 it will be None.
      ioa: A float numpy array of size [num_detected_boxes, num_gt_boxes]. If
          gt_group_of_boxlist.num_boxes() == 0 it will be None.
      scores: The score of the detected boxlist.
      num_boxes: Number of non-maximum suppressed detected boxes.
    """
    detected_boxlist = np_box_list.BoxList(detected_boxes)
    detected_boxlist.add_field('scores', detected_scores)
    detected_boxlist = np_box_list_ops.non_max_suppression(
        detected_boxlist, self.nms_max_output_boxes, self.nms_iou_threshold)
    gt_non_group_of_boxlist = np_box_list.BoxList(
        groundtruth_boxes[~groundtruth_is_group_of_list])
    gt_group_of_boxlist = np_box_list.BoxList(
        groundtruth_boxes[groundtruth_is_group_of_list])
    iou = np_box_list_ops.iou(detected_boxlist, gt_non_group_of_boxlist)
    ioa = np_box_list_ops.ioa(gt_group_of_boxlist, detected_boxlist)
    scores = detected_boxlist.get_field('scores')
    num_boxes = detected_boxlist.num_boxes()
    return iou, ioa, scores, num_boxes

开发者ID:cagbal，项目名称:ros_people_object_detection_tensorflow，代码行数:42，代码来源:per_image_evaluation.py

示例4: _get_overlaps_and_scores_box_mode

# 需要导入模块: from object_detection.utils import np_box_mask_list_ops [as 别名]
# 或者: from object_detection.utils.np_box_mask_list_ops import ioa [as 别名]
def _get_overlaps_and_scores_box_mode(self, detected_boxes, detected_scores,
                                        groundtruth_boxes,
                                        groundtruth_is_group_of_list):
    """Computes overlaps and scores between detected and groudntruth boxes.

    Args:
      detected_boxes: A numpy array of shape [N, 4] representing detected box
        coordinates
      detected_scores: A 1-d numpy array of length N representing classification
        score
      groundtruth_boxes: A numpy array of shape [M, 4] representing ground truth
        box coordinates
      groundtruth_is_group_of_list: A boolean numpy array of length M denoting
        whether a ground truth box has group-of tag. If a groundtruth box is
        group-of box, every detection matching this box is ignored.

    Returns:
      iou: A float numpy array of size [num_detected_boxes, num_gt_boxes]. If
          gt_non_group_of_boxlist.num_boxes() == 0 it will be None.
      ioa: A float numpy array of size [num_detected_boxes, num_gt_boxes]. If
          gt_group_of_boxlist.num_boxes() == 0 it will be None.
      scores: The score of the detected boxlist.
      num_boxes: Number of non-maximum suppressed detected boxes.
    """
    detected_boxlist = np_box_list.BoxList(detected_boxes)
    detected_boxlist.add_field('scores', detected_scores)
    detected_boxlist = np_box_list_ops.non_max_suppression(
        detected_boxlist, self.nms_max_output_boxes, self.nms_iou_threshold)
    gt_non_group_of_boxlist = np_box_list.BoxList(
        groundtruth_boxes[~groundtruth_is_group_of_list])
    gt_group_of_boxlist = np_box_list.BoxList(
        groundtruth_boxes[groundtruth_is_group_of_list])
    iou = np_box_list_ops.iou(detected_boxlist, gt_non_group_of_boxlist)
    ioa = np.transpose(
        np_box_list_ops.ioa(gt_group_of_boxlist, detected_boxlist))
    scores = detected_boxlist.get_field('scores')
    num_boxes = detected_boxlist.num_boxes()
    return iou, ioa, scores, num_boxes

开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:40，代码来源:per_image_evaluation.py

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