dfe26d7233aaccb1d344ff9ba9995d722503b7e7,luminoth/models/ssd/ssd.py,SSD,_build,#SSD#,62

Before Change

            // during training due to hard negative mining.
            // We use class_targets to know which ones to ignore (they
            // are marked as -1 if they are to be ignored)
            if is_training:
                with tf.name_scope("prepare_batch"):
                    predictions_filter = tf.greater_equal(class_targets, 0)

                    target_anchors = tf.boolean_mask(
                        all_anchors, predictions_filter)
                    bbox_offsets_targets = tf.boolean_mask(
                        bbox_offsets_targets, predictions_filter)
                    class_targets = tf.boolean_mask(
                        class_targets, predictions_filter)
                    class_scores = tf.boolean_mask(
                        class_scores, predictions_filter)
                    class_probabilities = tf.boolean_mask(
                        class_probabilities, predictions_filter)
                    bbox_offsets = tf.boolean_mask(
                        bbox_offsets, predictions_filter)

            prediction_dict["target"] = {
                "cls": class_targets,
                "bbox_offsets": bbox_offsets_targets,
                "anchors": target_anchors

After Change

                tf.cast(tf.shape(image)[1:3], tf.float32)
            )
            prediction_dict["classification_prediction"] = proposals
        if not is_training:
            // Generate proposals for prediction
            proposals = proposals_creator(
                class_probabilities, bbox_offsets, all_anchors,
                tf.cast(tf.shape(image)[1:3], tf.float32)
            )
            prediction_dict["classification_prediction"] = proposals 

        prediction_dict["cls_pred"] = class_scores
        prediction_dict["loc_pred"] = bbox_offsets

        if self._debug:

Instances