function remove_low_and_no_objects(class_logits, mask_logits, object_mask_threshold, num_labels) {

    const mask_probs_item = [];
    const pred_scores_item = [];
    const pred_labels_item = [];

    for (let j = 0; j < class_logits.dims[0]; ++j) {
        const cls = class_logits[j];
        const mask = mask_logits[j];

        const pred_label = max(cls.data)[1];
        if (pred_label === num_labels) {
            // Is the background, so we ignore it
            continue;
        }

        const scores = softmax(cls.data);
        const pred_score = scores[pred_label];
        if (pred_score > object_mask_threshold) {
            mask_probs_item.push(mask);
            pred_scores_item.push(pred_score);
            pred_labels_item.push(pred_label);
        }
    }

    return [mask_probs_item, pred_scores_item, pred_labels_item];
}
Binarize the given masks using `object_mask_threshold`, it returns the associated values of `masks`, `scores` and `labels`.
@param {Tensor} class_logits The class logits.
@param {Tensor} mask_logits The mask logits.
@param {number} object_mask_threshold A number between 0 and 1 used to binarize the masks.
@param {number} num_labels The number of labels.
@returns {[Tensor[], number[], number[]]} The binarized masks, the scores, and the labels.
@private