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import sys
class CONFIG:
# DEBUG Settings
DRY_RUN = False
DRY_RUN_MAX_IMAGES = 10
# Pipeline settings
NUM_CORES = 2
MAST3R_MIN_PAIR = 15
MATCH_CONF_TH = 1.001
!pip install torch torchvision torchaudio --no-index --find-links=/kaggle/input/mast3r-fix/mast3r-wheels
!pip install faiss-gpu-cu12 --no-index --find-links=/kaggle/input/mast3r-fix/mast3r-wheels
# 离线安装所有依赖（不联网）
!pip install --no-index --find-links=/kaggle/input/mast3r-fix/mast3r-wheels \
-r /kaggle/input/mast3r-fix/mast3r/requirements.txt \
-r /kaggle/input/mast3r-fix/mast3r/dust3r/requirements.txt \
-r /kaggle/input/mast3r-fix/mast3r/dust3r/requirements_optional.txt
!pip install --no-index /kaggle/input/imc2024-packages-lightglue-rerun-kornia/* --no-deps
!pip install --no-index /kaggle/input/pycolmap3-11/pycolmap-3.11.1-cp311-cp311-manylinux_2_28_x86_64.whl --no-deps
# !pip install kornia_rs
# !pip install pycolmap
# 加入源码主目录（包含 mast3r, dust3r 等子目录）
sys.path.insert(0, "/kaggle/input/mast3r-fix/mast3r")
sys.path.insert(0, '/kaggle/input/mast3r-fix/mast3r/asmk')
sys.path.insert(0, '/kaggle/input/mast3r-fix/mast3r/dust3r/croco/models/curope')
!rm -rf /kaggle/working/visualization_output
!rm -rf /kaggle/working/temp
!rm -rf /kaggle/working/result
import random
import os
import numpy as np
import torch
import dataclasses
def seed_everything(seed: int = 42):
"""Set seed for reproducibility across random, numpy, torch (CPU + CUDA)."""
random.seed(seed)
np.random.seed(seed)
os.environ["PYTHONHASHSEED"] = str(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed) # for multi-GPU
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
seed_everything()
import pycolmap
!pip show pycolmap
import pycolmap
import os
print(os.listdir(os.path.dirname(pycolmap.__file__)))
import sys
import os
from tqdm import tqdm
from time import time, sleep
import gc
import numpy as np
import h5py
import dataclasses
import pandas as pd
from IPython.display import clear_output
from collections import defaultdict
from copy import deepcopy
from PIL import Image
import cv2
import torch
import torch.nn.functional as F
import torch
from transformers import AutoImageProcessor, AutoModel
# IMPORTANT Utilities: importing data into colmap and competition metric
import pycolmap
sys.path.append('/kaggle/input/pycolmap3-11-imc-utils')
# from database import *
from h5_to_db import *
import metric
from pycolmap import verify_matches, TwoViewGeometryOptions
from fastprogress import progress_bar
# 主线程先 preload，确保子线程里不会挂
_ = verify_matches
_ = TwoViewGeometryOptions()
from mast3r.model import AsymmetricMASt3R
from mast3r.fast_nn import fast_reciprocal_NNs, extract_correspondences_nonsym
import mast3r.utils.path_to_dust3r
from dust3r.inference import inference
from dust3r.utils.image import load_images
!rm -rf /kaggle/working/result
# Configuration
import torch
device = 'cuda' if torch.cuda.is_available() else 'cpu' # Automatically use GPU if available
print(f"Using device: {device}")