Python eval_util.get_eval_metric_ops_for_evaluators方法代碼示例

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

在下文中一共展示了eval_util.get_eval_metric_ops_for_evaluators方法的13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_get_eval_metric_ops_for_coco_detections

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections(self, batch_size=1,
                                                   max_gt_boxes=None,
                                                   scale_to_absolute=False):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(['coco_detection_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(batch_size=batch_size,
                                           max_gt_boxes=max_gt_boxes,
                                           scale_to_absolute=scale_to_absolute)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op = metric_ops['DetectionBoxes_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertNotIn('DetectionMasks_Precision/mAP', metrics)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:23，代碼來源:eval_util_test.py

示例2: test_get_eval_metric_ops_for_coco_detections_and_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_masks(
      self, batch_size=1, max_gt_boxes=None, scale_to_absolute=False):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(
        ['coco_detection_metrics', 'coco_mask_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(batch_size=batch_size,
                                           max_gt_boxes=max_gt_boxes,
                                           scale_to_absolute=scale_to_absolute)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:25，代碼來源:eval_util_test.py

示例3: test_get_eval_metric_ops_for_coco_detections_and_resized_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_resized_masks(
      self, batch_size=1, max_gt_boxes=None, scale_to_absolute=False):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(
        ['coco_detection_metrics', 'coco_mask_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(batch_size=batch_size,
                                           max_gt_boxes=max_gt_boxes,
                                           scale_to_absolute=scale_to_absolute,
                                           resized_groundtruth_masks=True)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:26，代碼來源:eval_util_test.py

示例4: test_get_eval_metric_ops_for_coco_detections

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections(self):
    evaluation_metrics = ['coco_detection_metrics']
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict()
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        evaluation_metrics, categories, eval_dict)
    _, update_op = metric_ops['DetectionBoxes_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op)
      metrics = sess.run(metrics)
      print(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertNotIn('DetectionMasks_Precision/mAP', metrics)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:19，代碼來源:eval_util_test.py

示例5: test_get_eval_metric_ops_for_coco_detections_and_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_masks(self):
    evaluation_metrics = ['coco_detection_metrics',
                          'coco_mask_metrics']
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict()
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        evaluation_metrics, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:21，代碼來源:eval_util_test.py

示例6: test_get_eval_metric_ops_for_coco_detections

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections(self):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(['coco_detection_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict()
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op = metric_ops['DetectionBoxes_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op)
      metrics = sess.run(metrics)
      print(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertNotIn('DetectionMasks_Precision/mAP', metrics)

開發者ID:BMW-InnovationLab，項目名稱:BMW-TensorFlow-Training-GUI，代碼行數:20，代碼來源:eval_util_test.py

示例7: test_get_eval_metric_ops_for_coco_detections_and_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_masks(self):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(
        ['coco_detection_metrics', 'coco_mask_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict()
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:BMW-InnovationLab，項目名稱:BMW-TensorFlow-Training-GUI，代碼行數:22，代碼來源:eval_util_test.py

示例8: test_get_eval_metric_ops_for_coco_detections_and_resized_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_resized_masks(self):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(
        ['coco_detection_metrics', 'coco_mask_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(resized_groundtruth_masks=True)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in metric_ops.iteritems():
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:BMW-InnovationLab，項目名稱:BMW-TensorFlow-Training-GUI，代碼行數:22，代碼來源:eval_util_test.py

示例9: test_get_eval_metric_ops_for_coco_detections

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections(self, batch_size=1,
                                                   max_gt_boxes=None,
                                                   scale_to_absolute=False):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(['coco_detection_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(batch_size=batch_size,
                                           max_gt_boxes=max_gt_boxes,
                                           scale_to_absolute=scale_to_absolute)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op = metric_ops['DetectionBoxes_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in six.iteritems(metric_ops):
        metrics[key] = value_op
      sess.run(update_op)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertNotIn('DetectionMasks_Precision/mAP', metrics)

開發者ID:tensorflow，項目名稱:models，代碼行數:23，代碼來源:eval_util_test.py

示例10: test_get_eval_metric_ops_for_coco_detections_and_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_masks(
      self, batch_size=1, max_gt_boxes=None, scale_to_absolute=False):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(
        ['coco_detection_metrics', 'coco_mask_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(batch_size=batch_size,
                                           max_gt_boxes=max_gt_boxes,
                                           scale_to_absolute=scale_to_absolute)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in six.iteritems(metric_ops):
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:tensorflow，項目名稱:models，代碼行數:25，代碼來源:eval_util_test.py

示例11: test_get_eval_metric_ops_for_coco_detections_and_resized_masks

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_for_coco_detections_and_resized_masks(
      self, batch_size=1, max_gt_boxes=None, scale_to_absolute=False):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(
        ['coco_detection_metrics', 'coco_mask_metrics'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict(batch_size=batch_size,
                                           max_gt_boxes=max_gt_boxes,
                                           scale_to_absolute=scale_to_absolute,
                                           resized_groundtruth_masks=True)
    metric_ops = eval_util.get_eval_metric_ops_for_evaluators(
        eval_config, categories, eval_dict)
    _, update_op_boxes = metric_ops['DetectionBoxes_Precision/mAP']
    _, update_op_masks = metric_ops['DetectionMasks_Precision/mAP']

    with self.test_session() as sess:
      metrics = {}
      for key, (value_op, _) in six.iteritems(metric_ops):
        metrics[key] = value_op
      sess.run(update_op_boxes)
      sess.run(update_op_masks)
      metrics = sess.run(metrics)
      self.assertAlmostEqual(1.0, metrics['DetectionBoxes_Precision/mAP'])
      self.assertAlmostEqual(1.0, metrics['DetectionMasks_Precision/mAP'])

開發者ID:tensorflow，項目名稱:models，代碼行數:26，代碼來源:eval_util_test.py

示例12: test_get_eval_metric_ops_raises_error_with_unsupported_metric

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_raises_error_with_unsupported_metric(self):
    eval_config = eval_pb2.EvalConfig()
    eval_config.metrics_set.extend(['unsupported_metric'])
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict()
    with self.assertRaises(ValueError):
      eval_util.get_eval_metric_ops_for_evaluators(
          eval_config, categories, eval_dict)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:10，代碼來源:eval_util_test.py

示例13: test_get_eval_metric_ops_raises_error_with_unsupported_metric

# 需要導入模塊: from object_detection import eval_util [as 別名]
# 或者: from object_detection.eval_util import get_eval_metric_ops_for_evaluators [as 別名]
def test_get_eval_metric_ops_raises_error_with_unsupported_metric(self):
    evaluation_metrics = ['unsupported_metrics']
    categories = self._get_categories_list()
    eval_dict = self._make_evaluation_dict()
    with self.assertRaises(ValueError):
      eval_util.get_eval_metric_ops_for_evaluators(
          evaluation_metrics, categories, eval_dict)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:9，代碼來源:eval_util_test.py

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