def knn_match_and_make_predictions()

in isc/descriptor_matching.py [0:0]

• 22 lines of code
• 6 McCabe index (conditional complexity)

def knn_match_and_make_predictions(xq, query_image_ids, xb, db_image_ids, k, ngpu=-1, metric=faiss.METRIC_L2):

    if faiss.get_num_gpus() == 0 or ngpu == 0:
        D, I = faiss.knn(xq, xb, k, metric)
    else:
        d = xq.shape[1]
        index = faiss.IndexFlat(d, metric)
        index.add(xb)
        index = faiss.index_cpu_to_all_gpus(index)
        D, I = index.search(xq, k=k)
    nq = len(xq)

    if metric == faiss.METRIC_L2:
        # use negated distances as scores
        D = -D

    predictions = [
        PredictedMatch(
            query_image_ids[i],
            db_image_ids[I[i, j]],
            D[i, j]
        )
        for i in range(nq)
        for j in range(k)
    ]
    return predictions