#!/usr/bin/env python3
# Copyright (C) 2024-present Naver Corporation. All rights reserved.
# Licensed under CC BY-NC-SA 4.0 (non-commercial use only).
#
# --------------------------------------------------------
# gradio demo executable
# --------------------------------------------------------
import os
import torch
import tempfile
from contextlib import nullcontext

from mast3r.demo import get_args_parser, main_demo

from mast3r.model import AsymmetricMASt3R
from mast3r.utils.misc import hash_md5

import mast3r.utils.path_to_dust3r  # noqa
from dust3r.demo import set_print_with_timestamp

import matplotlib.pyplot as pl

pl.ion()

torch.backends.cuda.matmul.allow_tf32 = True  # for gpu >= Ampere and pytorch >= 1.12

if __name__ == "__main__":
    parser = get_args_parser()
    args = parser.parse_args()
    set_print_with_timestamp()

    if args.server_name is not None:
        server_name = args.server_name
    else:
        server_name = "0.0.0.0" if args.local_network else "127.0.0.1"

    if args.weights is not None:
        weights_path = args.weights
    else:
        weights_path = "naver/" + args.model_name

    model = AsymmetricMASt3R.from_pretrained(weights_path).to(args.device)
    chkpt_tag = hash_md5(weights_path)

    def get_context(tmp_dir):
        return tempfile.TemporaryDirectory(suffix="_mast3r_gradio_demo") if tmp_dir is None else nullcontext(tmp_dir)

    with get_context(args.tmp_dir) as tmpdirname:
        cache_path = os.path.join(tmpdirname, chkpt_tag)
        os.makedirs(cache_path, exist_ok=True)
        main_demo(
            cache_path,
            model,
            args.device,
            args.image_size,
            server_name,
            args.server_port,
            silent=args.silent,
            share=args.share,
            gradio_delete_cache=args.gradio_delete_cache,
        )
