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research/object_detection/predictors/convolutional_box_predictor.py

Summary

Maintainability
D
2 days
Test Coverage

File convolutional_box_predictor.py has 359 lines of code (exceeds 250 allowed). Consider refactoring.
Open

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
Severity: Minor
Found in research/object_detection/predictors/convolutional_box_predictor.py - About 4 hrs to fix

    Function _predict has a Cognitive Complexity of 16 (exceeds 5 allowed). Consider refactoring.
    Open

      def _predict(self, image_features, num_predictions_per_location_list):
    """Computes encoded object locations and corresponding confidences.

    Args:
      image_features: A list of float tensors of shape [batch_size, height_i,
    Severity: Minor
    Found in research/object_detection/predictors/convolutional_box_predictor.py - About 2 hrs to fix

    Cognitive Complexity

    Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

    A method's cognitive complexity is based on a few simple rules:

    • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
    • Code is considered more complex for each "break in the linear flow of the code"
    • Code is considered more complex when "flow breaking structures are nested"

    Further reading

    Function _predict has a Cognitive Complexity of 14 (exceeds 5 allowed). Consider refactoring.
    Open

      def _predict(self, image_features, num_predictions_per_location_list):
    """Computes encoded object locations and corresponding confidences.

    Args:
      image_features: A list of float tensors of shape [batch_size, height_i,
    Severity: Minor
    Found in research/object_detection/predictors/convolutional_box_predictor.py - About 1 hr to fix

    Cognitive Complexity

    Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

    A method's cognitive complexity is based on a few simple rules:

    • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
    • Code is considered more complex for each "break in the linear flow of the code"
    • Code is considered more complex when "flow breaking structures are nested"

    Further reading

    Function __init__ has 12 arguments (exceeds 4 allowed). Consider refactoring.
    Open

      def __init__(self,
    Severity: Major
    Found in research/object_detection/predictors/convolutional_box_predictor.py - About 1 hr to fix

      Function __init__ has 9 arguments (exceeds 4 allowed). Consider refactoring.
      Open

        def __init__(self,
      Severity: Major
      Found in research/object_detection/predictors/convolutional_box_predictor.py - About 1 hr to fix

        Function _predict_head has 6 arguments (exceeds 4 allowed). Consider refactoring.
        Open

          def _predict_head(self, head_name, head_obj, image_feature, box_tower_feature,
        Severity: Minor
        Found in research/object_detection/predictors/convolutional_box_predictor.py - About 45 mins to fix

          Avoid deeply nested control flow statements.
          Open

                      for head_name in sorted_keys:
              if head_name == CLASS_PREDICTIONS_WITH_BACKGROUND:
                head_obj = self._class_prediction_head
              else:
                head_obj = self._other_heads[head_name]
          Severity: Major
          Found in research/object_detection/predictors/convolutional_box_predictor.py - About 45 mins to fix

            Avoid deeply nested control flow statements.
            Open

                        for head_name in sorted_keys:
              if head_name == BOX_ENCODINGS:
                head_obj = self._box_prediction_head
              elif head_name == CLASS_PREDICTIONS_WITH_BACKGROUND:
                head_obj = self._class_prediction_head
            Severity: Major
            Found in research/object_detection/predictors/convolutional_box_predictor.py - About 45 mins to fix

              Avoid deeply nested control flow statements.
              Open

                          if self._share_prediction_tower:
              box_tower_scope = 'PredictionTower'
            else:
              box_tower_scope = 'BoxPredictionTower'
            box_tower_feature = self._compute_base_tower(
              Severity: Major
              Found in research/object_detection/predictors/convolutional_box_predictor.py - About 45 mins to fix

                Avoid deeply nested control flow statements.
                Open

                            if depth > 0 and self._num_layers_before_predictor > 0:
              for i in range(self._num_layers_before_predictor):
                net = slim.conv2d(
                    net,
                    depth, [1, 1],
                Severity: Major
                Found in research/object_detection/predictors/convolutional_box_predictor.py - About 45 mins to fix

                  Function _compute_base_tower has a Cognitive Complexity of 8 (exceeds 5 allowed). Consider refactoring.
                  Open

                    def _compute_base_tower(self, tower_name_scope, image_feature, feature_index):
    net = image_feature
    for i in range(self._num_layers_before_predictor):
      if self._use_depthwise:
        conv_op = functools.partial(slim.separable_conv2d, depth_multiplier=1)
                  Severity: Minor
                  Found in research/object_detection/predictors/convolutional_box_predictor.py - About 45 mins to fix

                  Cognitive Complexity

                  Cognitive Complexity is a measure of how difficult a unit of code is to intuitively understand. Unlike Cyclomatic Complexity, which determines how difficult your code will be to test, Cognitive Complexity tells you how difficult your code will be to read and comprehend.

                  A method's cognitive complexity is based on a few simple rules:

                  • Code is not considered more complex when it uses shorthand that the language provides for collapsing multiple statements into one
                  • Code is considered more complex for each "break in the linear flow of the code"
                  • Code is considered more complex when "flow breaking structures are nested"

                  Further reading

                  Identical blocks of code found in 2 locations. Consider refactoring.
                  Open

                      if has_different_feature_channels:
      inserted_layer_counter = 0
      target_channel = max(set(feature_channels), key=feature_channels.count)
      tf.logging.info('Not all feature maps have the same number of '
                      'channels, found: {}, appending additional projection '
                  Severity: Major
                  Found in research/object_detection/predictors/convolutional_box_predictor.py and 1 other location - About 2 hrs to fix
                  research/object_detection/predictors/convolutional_keras_box_predictor.py on lines 402..412

                  Duplicated Code

                  Duplicated code can lead to software that is hard to understand and difficult to change. The Don't Repeat Yourself (DRY) principle states:

                  Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.

                  When you violate DRY, bugs and maintenance problems are sure to follow. Duplicated code has a tendency to both continue to replicate and also to diverge (leaving bugs as two similar implementations differ in subtle ways).

                  Tuning

                  This issue has a mass of 57.

                  We set useful threshold defaults for the languages we support but you may want to adjust these settings based on your project guidelines.

                  The threshold configuration represents the minimum mass a code block must have to be analyzed for duplication. The lower the threshold, the more fine-grained the comparison.

                  If the engine is too easily reporting duplication, try raising the threshold. If you suspect that the engine isn't catching enough duplication, try lowering the threshold. The best setting tends to differ from language to language.

                  See codeclimate-duplication's documentation for more information about tuning the mass threshold in your .codeclimate.yml.

                  Refactorings

                  Further Reading

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