945fd5534c8903f928084a14e494cc00b0d6c040,keras_rcnn/layers/losses/_rpn.py,RPN,call,#RPN#Any#,15

Before Change

        self.add_loss(loss)

        return scores_output

    def compute_classification_loss(self, output, target):
        pass

After Change

    def call(self, inputs, **kwargs):
        output_bounding_boxes, target_bounding_boxes, output_scores, target_scores = inputs

        output_scores = keras.backend.reshape(output_scores, (1, -1))

        classification_loss = self.compute_classification_loss(output_scores, target_scores)

        output_bounding_boxes = keras.backend.reshape(output_bounding_boxes, (1, -1, 4))

        regression_loss = self.compute_regression_loss(output_bounding_boxes, target_bounding_boxes, output_scores)

        loss = classification_loss + regression_loss

        self.add_loss(loss)

        return [output_bounding_boxes, output_scores]

    @staticmethod
    def compute_classification_loss(output, target):
        condition = keras.backend.not_equal(target, -1)

Instances