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import argparse | |
import multiprocessing | |
import shutil | |
from pathlib import Path | |
from typing import Any, Dict, List, Optional | |
import pycolmap | |
from . import logger | |
from .triangulation import ( | |
OutputCapture, | |
estimation_and_geometric_verification, | |
import_features, | |
import_matches, | |
parse_option_args, | |
) | |
from .utils.database import COLMAPDatabase | |
def create_empty_db(database_path: Path): | |
if database_path.exists(): | |
logger.warning("The database already exists, deleting it.") | |
database_path.unlink() | |
logger.info("Creating an empty database...") | |
db = COLMAPDatabase.connect(database_path) | |
db.create_tables() | |
db.commit() | |
db.close() | |
def import_images( | |
image_dir: Path, | |
database_path: Path, | |
camera_mode: pycolmap.CameraMode, | |
image_list: Optional[List[str]] = None, | |
options: Optional[Dict[str, Any]] = None, | |
): | |
logger.info("Importing images into the database...") | |
if options is None: | |
options = {} | |
images = list(image_dir.iterdir()) | |
if len(images) == 0: | |
raise IOError(f"No images found in {image_dir}.") | |
with pycolmap.ostream(): | |
pycolmap.import_images( | |
database_path, | |
image_dir, | |
camera_mode, | |
image_list=image_list or [], | |
options=options, | |
) | |
def get_image_ids(database_path: Path) -> Dict[str, int]: | |
db = COLMAPDatabase.connect(database_path) | |
images = {} | |
for name, image_id in db.execute("SELECT name, image_id FROM images;"): | |
images[name] = image_id | |
db.close() | |
return images | |
def run_reconstruction( | |
sfm_dir: Path, | |
database_path: Path, | |
image_dir: Path, | |
verbose: bool = False, | |
options: Optional[Dict[str, Any]] = None, | |
) -> pycolmap.Reconstruction: | |
models_path = sfm_dir / "models" | |
models_path.mkdir(exist_ok=True, parents=True) | |
logger.info("Running 3D reconstruction...") | |
if options is None: | |
options = {} | |
options = {"num_threads": min(multiprocessing.cpu_count(), 16), **options} | |
with OutputCapture(verbose): | |
with pycolmap.ostream(): | |
reconstructions = pycolmap.incremental_mapping( | |
database_path, image_dir, models_path, options=options | |
) | |
if len(reconstructions) == 0: | |
logger.error("Could not reconstruct any model!") | |
return None | |
logger.info(f"Reconstructed {len(reconstructions)} model(s).") | |
largest_index = None | |
largest_num_images = 0 | |
for index, rec in reconstructions.items(): | |
num_images = rec.num_reg_images() | |
if num_images > largest_num_images: | |
largest_index = index | |
largest_num_images = num_images | |
assert largest_index is not None | |
logger.info( | |
f"Largest model is #{largest_index} " | |
f"with {largest_num_images} images." | |
) | |
for filename in ["images.bin", "cameras.bin", "points3D.bin"]: | |
if (sfm_dir / filename).exists(): | |
(sfm_dir / filename).unlink() | |
shutil.move( | |
str(models_path / str(largest_index) / filename), str(sfm_dir) | |
) | |
return reconstructions[largest_index] | |
def main( | |
sfm_dir: Path, | |
image_dir: Path, | |
pairs: Path, | |
features: Path, | |
matches: Path, | |
camera_mode: pycolmap.CameraMode = pycolmap.CameraMode.AUTO, | |
verbose: bool = False, | |
skip_geometric_verification: bool = False, | |
min_match_score: Optional[float] = None, | |
image_list: Optional[List[str]] = None, | |
image_options: Optional[Dict[str, Any]] = None, | |
mapper_options: Optional[Dict[str, Any]] = None, | |
) -> pycolmap.Reconstruction: | |
assert features.exists(), features | |
assert pairs.exists(), pairs | |
assert matches.exists(), matches | |
sfm_dir.mkdir(parents=True, exist_ok=True) | |
database = sfm_dir / "database.db" | |
create_empty_db(database) | |
import_images(image_dir, database, camera_mode, image_list, image_options) | |
image_ids = get_image_ids(database) | |
import_features(image_ids, database, features) | |
import_matches( | |
image_ids, | |
database, | |
pairs, | |
matches, | |
min_match_score, | |
skip_geometric_verification, | |
) | |
if not skip_geometric_verification: | |
estimation_and_geometric_verification(database, pairs, verbose) | |
reconstruction = run_reconstruction( | |
sfm_dir, database, image_dir, verbose, mapper_options | |
) | |
if reconstruction is not None: | |
logger.info( | |
f"Reconstruction statistics:\n{reconstruction.summary()}" | |
+ f"\n\tnum_input_images = {len(image_ids)}" | |
) | |
return reconstruction | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser() | |
parser.add_argument("--sfm_dir", type=Path, required=True) | |
parser.add_argument("--image_dir", type=Path, required=True) | |
parser.add_argument("--pairs", type=Path, required=True) | |
parser.add_argument("--features", type=Path, required=True) | |
parser.add_argument("--matches", type=Path, required=True) | |
parser.add_argument( | |
"--camera_mode", | |
type=str, | |
default="AUTO", | |
choices=list(pycolmap.CameraMode.__members__.keys()), | |
) | |
parser.add_argument("--skip_geometric_verification", action="store_true") | |
parser.add_argument("--min_match_score", type=float) | |
parser.add_argument("--verbose", action="store_true") | |
parser.add_argument( | |
"--image_options", | |
nargs="+", | |
default=[], | |
help="List of key=value from {}".format( | |
pycolmap.ImageReaderOptions().todict() | |
), | |
) | |
parser.add_argument( | |
"--mapper_options", | |
nargs="+", | |
default=[], | |
help="List of key=value from {}".format( | |
pycolmap.IncrementalMapperOptions().todict() | |
), | |
) | |
args = parser.parse_args().__dict__ | |
image_options = parse_option_args( | |
args.pop("image_options"), pycolmap.ImageReaderOptions() | |
) | |
mapper_options = parse_option_args( | |
args.pop("mapper_options"), pycolmap.IncrementalMapperOptions() | |
) | |
main(**args, image_options=image_options, mapper_options=mapper_options) | |