First column (class id) is -1 for negative detections
        :param detections:
        :return:

def filter_positive_detections(detections):
        """
        First column (class id) is -1 for negative detections
        :param detections:
        :return:
        """
        class_idx = 0
        assert(isinstance(detections, mx.nd.NDArray) or isinstance(detections, np.ndarray))
        detections_per_image = []
        # for each image
        for i in range(detections.shape[0]):
            result = []
            det = detections[i, :, :]
            for obj in det:
                if obj[class_idx] >= 0:
                    result.append(obj)
            detections_per_image.append(result)
        logging.info("%d positive detections", len(result))
        return detections_per_image