3676970a96bd66646b4cf40991e319e34154bc97,rastervision/evaluation/semantic_segmentation_evaluation.py,SemanticSegmentationEvaluation,compute,#SemanticSegmentationEvaluation#Any#Any#,72

Before Change

            gt_arr = gt_labels.get_label_arr(window)
            pred_arr = pred_labels.get_label_arr(window)

            eval_items = []
            for class_id in self.class_map.get_keys():
                if class_id > 0:
                    eval_item = get_class_eval_item(gt_arr, pred_arr, class_id,
                                                    self.class_map)

After Change

        self.clear()

        labels = np.arange(len(self.class_map) + 1)
        conf_mat = np.zeros((len(self.class_map) + 1, ) * 2)
        for window in pred_labels.get_windows():
            log.debug("Evaluating window: {}".format(window))
            gt_arr = gt_labels.get_label_arr(window).ravel()
            pred_arr = pred_labels.get_label_arr(window).ravel()
            conf_mat += confusion_matrix(gt_arr, pred_arr, labels=labels)

        for class_id in self.class_map.get_keys():
            if class_id > 0:
                self.class_to_eval_item[class_id] = get_class_eval_item(
                    conf_mat, class_id, self.class_map)
        self.compute_avg()

    def compute_vector(self, gt, pred, mode, class_id):
        Compute evaluation over vector predictions.

Instances