# Copyright (C) 2022-present Naver Corporation. All rights reserved.
# Licensed under CC BY-NC-SA 4.0 (non-commercial use only).

import os
from torch.utils.data import Dataset
from PIL import Image

from datasets.transforms import get_pair_transforms


def load_image(impath):
    return Image.open(impath)


def load_pairs_from_cache_file(fname, root=""):
    assert os.path.isfile(fname), "cannot parse pairs from {:s}, file does not exist".format(fname)
    with open(fname, "r") as fid:
        lines = fid.read().strip().splitlines()
    pairs = [(os.path.join(root, l.split()[0]), os.path.join(root, l.split()[1])) for l in lines]
    return pairs


def load_pairs_from_list_file(fname, root=""):
    assert os.path.isfile(fname), "cannot parse pairs from {:s}, file does not exist".format(fname)
    with open(fname, "r") as fid:
        lines = fid.read().strip().splitlines()
    pairs = [
        (os.path.join(root, l + "_1.jpg"), os.path.join(root, l + "_2.jpg")) for l in lines if not l.startswith("#")
    ]
    return pairs


def write_cache_file(fname, pairs, root=""):
    if len(root) > 0:
        if not root.endswith("/"):
            root += "/"
        assert os.path.isdir(root)
    s = ""
    for im1, im2 in pairs:
        if len(root) > 0:
            assert im1.startswith(root), im1
            assert im2.startswith(root), im2
        s += "{:s} {:s}\n".format(im1[len(root) :], im2[len(root) :])
    with open(fname, "w") as fid:
        fid.write(s[:-1])


def parse_and_cache_all_pairs(dname, data_dir="./data/"):
    if dname == "habitat_release":
        dirname = os.path.join(data_dir, "habitat_release")
        assert os.path.isdir(dirname), "cannot find folder for habitat_release pairs: " + dirname
        cache_file = os.path.join(dirname, "pairs.txt")
        assert not os.path.isfile(cache_file), "cache file already exists: " + cache_file

        print("Parsing pairs for dataset: " + dname)
        pairs = []
        for root, dirs, files in os.walk(dirname):
            if "val" in root:
                continue
            dirs.sort()
            pairs += [
                (os.path.join(root, f), os.path.join(root, f[: -len("_1.jpeg")] + "_2.jpeg"))
                for f in sorted(files)
                if f.endswith("_1.jpeg")
            ]
        print("Found {:,} pairs".format(len(pairs)))
        print("Writing cache to: " + cache_file)
        write_cache_file(cache_file, pairs, root=dirname)

    else:
        raise NotImplementedError("Unknown dataset: " + dname)


def dnames_to_image_pairs(dnames, data_dir="./data/"):
    """
    dnames: list of datasets with image pairs, separated by +
    """
    all_pairs = []
    for dname in dnames.split("+"):
        if dname == "habitat_release":
            dirname = os.path.join(data_dir, "habitat_release")
            assert os.path.isdir(dirname), "cannot find folder for habitat_release pairs: " + dirname
            cache_file = os.path.join(dirname, "pairs.txt")
            assert os.path.isfile(cache_file), (
                "cannot find cache file for habitat_release pairs, please first create the cache file, see instructions. "
                + cache_file
            )
            pairs = load_pairs_from_cache_file(cache_file, root=dirname)
        elif dname in ["ARKitScenes", "MegaDepth", "3DStreetView", "IndoorVL"]:
            dirname = os.path.join(data_dir, dname + "_crops")
            assert os.path.isdir(dirname), "cannot find folder for {:s} pairs: {:s}".format(dname, dirname)
            list_file = os.path.join(dirname, "listing.txt")
            assert os.path.isfile(list_file), "cannot find list file for {:s} pairs, see instructions. {:s}".format(
                dname, list_file
            )
            pairs = load_pairs_from_list_file(list_file, root=dirname)
        print("  {:s}: {:,} pairs".format(dname, len(pairs)))
        all_pairs += pairs
    if "+" in dnames:
        print(" Total: {:,} pairs".format(len(all_pairs)))
    return all_pairs


class PairsDataset(Dataset):

    def __init__(self, dnames, trfs="", totensor=True, normalize=True, data_dir="./data/"):
        super().__init__()
        self.image_pairs = dnames_to_image_pairs(dnames, data_dir=data_dir)
        self.transforms = get_pair_transforms(transform_str=trfs, totensor=totensor, normalize=normalize)

    def __len__(self):
        return len(self.image_pairs)

    def __getitem__(self, index):
        im1path, im2path = self.image_pairs[index]
        im1 = load_image(im1path)
        im2 = load_image(im2path)
        if self.transforms is not None:
            im1, im2 = self.transforms(im1, im2)
        return im1, im2


if __name__ == "__main__":
    import argparse

    parser = argparse.ArgumentParser(prog="Computing and caching list of pairs for a given dataset")
    parser.add_argument("--data_dir", default="./data/", type=str, help="path where data are stored")
    parser.add_argument("--dataset", default="habitat_release", type=str, help="name of the dataset")
    args = parser.parse_args()
    parse_and_cache_all_pairs(dname=args.dataset, data_dir=args.data_dir)
