Пример #1
0
def getImgPathsAndRanksSorted(rows, db_path, class_id, diff, delta, trainFlag,
                              layer):

    rows_same_class = getImgInfoSameClass(db_path, class_id, trainFlag, layer)
    indices, img_paths = zip(*rows_same_class)
    assert list(indices) == sorted(indices)

    img_paths_all = []
    nn_ranks_all = []
    for row_curr in rows:

        img_path_curr, neighbor_index, azimuth_differences = row_curr
        idx_to_del = img_paths.index(img_path_curr)
        azimuth_differences[idx_to_del] = -1 * float('Inf')
        idx_of_interest = getIndexWithAngleDifference(azimuth_differences,
                                                      diff, delta)
        indices = np.array(indices)
        nn_rank, idx_to_order = experiments_super.sortBySmallestDistanceRank(
            indices[idx_of_interest], neighbor_index)
        img_paths_sorted = np.array(img_paths)[idx_of_interest][idx_to_order]

        img_paths_all.append(list(img_paths_sorted))
        nn_ranks_all.append(list(nn_rank))

    return img_paths_all, nn_ranks_all
Пример #2
0
def getImgPathsAndRanksSorted(rows, db_path, class_id, trainFlag, layer, pascalFlag):

    rows_same_class = getImgInfoSameClass(db_path, class_id, trainFlag, layer, pascalFlag)
    indices, img_paths = zip(*rows_same_class)
    assert list(indices) == sorted(indices)

    img_paths_all = []
    nn_ranks_all = []
    for row_curr in rows:

        img_path_curr, neighbor_index = row_curr
        idx_to_del = img_paths.index(img_path_curr)
        indices_copy = np.delete(indices, [idx_to_del])
        nn_rank, idx_to_order = experiments_super.sortBySmallestDistanceRank(indices_copy, neighbor_index)
        img_paths_sorted = np.array(img_paths)[idx_to_order]
        img_paths_all.append(list(img_paths_sorted))
        nn_ranks_all.append(list(nn_rank))

    return img_paths_all, nn_ranks_all
Пример #3
0
def getImgPathsAndRanksSorted(rows,db_path,class_id,diff,delta,trainFlag,layer):
    
    rows_same_class=getImgInfoSameClass(db_path,class_id,trainFlag,layer)
    indices,img_paths=zip(*rows_same_class);
    assert list(indices)==sorted(indices)

    img_paths_all=[];
    nn_ranks_all=[];
    for row_curr in rows:

        img_path_curr,neighbor_index,azimuth_differences=row_curr;
        idx_to_del=img_paths.index(img_path_curr);
        azimuth_differences[idx_to_del]=-1*float('Inf');
        idx_of_interest=getIndexWithAngleDifference(azimuth_differences,diff,delta)
        indices=np.array(indices);
        nn_rank,idx_to_order=experiments_super.sortBySmallestDistanceRank(indices[idx_of_interest],neighbor_index);
        img_paths_sorted=np.array(img_paths)[idx_of_interest][idx_to_order];
 
        img_paths_all.append(list(img_paths_sorted));
        nn_ranks_all.append(list(nn_rank));

    return img_paths_all,nn_ranks_all