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"""
File to import matchers. The module's import are within the functions, so that
a module is imported only iff needed, reducing the number of raised errors and
warnings due to unused modules.
"""
from pathlib import Path
from .utils import supress_stdout, add_to_path, get_default_device
from .im_models.base_matcher import BaseMatcher
# add viz2d from lightglue to namespace - thanks lightglue!
THIRD_PARTY_DIR = Path(__file__).parent.joinpath("third_party")
add_to_path(THIRD_PARTY_DIR.joinpath("LightGlue"))
from lightglue import viz2d # for quick import later 'from matching import viz2d'
WEIGHTS_DIR = Path(__file__).parent.joinpath("model_weights")
WEIGHTS_DIR.mkdir(exist_ok=True)
__version__ = "1.0.0"
available_models = [
"loftr",
"eloftr",
"se2loftr",
"xoftr",
"aspanformer",
"matchformer",
"sift-lg",
"superpoint-lg",
"disk-lg",
"aliked-lg",
"doghardnet-lg",
"roma",
"tiny-roma",
"dedode",
"steerers",
"affine-steerers",
"dedode-kornia",
"sift-nn",
"orb-nn",
"patch2pix",
"superglue",
"r2d2",
"d2net",
"duster",
"master",
"doghardnet-nn",
"xfeat",
"xfeat-star",
"xfeat-lg",
"xfeat-steerers-perm",
"xfeat-steerers-learned",
"xfeat-star-steerers-perm",
"xfeat-star-steerers-learned",
"dedode-lg",
"gim-dkm",
"gim-lg",
"omniglue",
"xfeat-subpx",
"xfeat-lg-subpx",
"dedode-subpx",
"splg-subpx",
"aliked-subpx",
"sift-sphereglue",
"superpoint-sphereglue",
"minima",
"minima-roma",
"minima-roma-tiny",
"minima-splg",
"minima-loftr",
"vggt"
]
def get_version(pkg):
version_num = pkg.__version__.split("-")[0]
major, minor, patch = [int(num) for num in version_num.split(".")]
return major, minor, patch
@supress_stdout
def get_matcher(
matcher_name="sift-lg", device="cpu", max_num_keypoints=2048, *args, **kwargs
):
if isinstance(matcher_name, list):
from matching.im_models.base_matcher import EnsembleMatcher
return EnsembleMatcher(matcher_name, device, *args, **kwargs)
if "subpx" in matcher_name:
from matching.im_models import keypt2subpx
detector_name = matcher_name.removesuffix("-subpx")
return keypt2subpx.Keypt2SubpxMatcher(
device, detector_name=detector_name, *args, **kwargs
)
if matcher_name == "loftr":
from matching.im_models import loftr
return loftr.LoftrMatcher(device, *args, **kwargs)
if matcher_name == "eloftr":
from matching.im_models import efficient_loftr
return efficient_loftr.EfficientLoFTRMatcher(device, *args, **kwargs)
if matcher_name == "se2loftr":
from matching.im_models import se2loftr
return se2loftr.Se2LoFTRMatcher(device, *args, **kwargs)
if matcher_name == "xoftr":
from matching.im_models import xoftr
return xoftr.XoFTRMatcher(device, *args, **kwargs)
elif matcher_name == "aspanformer":
from matching.im_models import aspanformer
return aspanformer.AspanformerMatcher(device, *args, **kwargs)
elif matcher_name == "matchformer":
from matching.im_models import matchformer
return matchformer.MatchformerMatcher(device, *args, **kwargs)
elif matcher_name == "sift-lg":
from matching.im_models import lightglue
return lightglue.SiftLightGlue(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "superpoint-lg":
from matching.im_models import lightglue
return lightglue.SuperpointLightGlue(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "disk-lg":
from matching.im_models import lightglue
return lightglue.DiskLightGlue(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "aliked-lg":
from matching.im_models import lightglue
return lightglue.AlikedLightGlue(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "doghardnet-lg":
from matching.im_models import lightglue
return lightglue.DognetLightGlue(device, max_num_keypoints, *args, **kwargs)
elif "roma" in matcher_name:
from matching.im_models import roma
if "tiny" in matcher_name:
return roma.TinyRomaMatcher(device, max_num_keypoints, *args, **kwargs)
else:
return roma.RomaMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "dedode":
from matching.im_models import dedode
return dedode.DedodeMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "dedode-kornia":
from matching.im_models import dedode
return dedode.DedodeKorniaMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "steerers":
from matching.im_models import steerers
return steerers.SteererMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name in ["aff-steerers", "affine-steerers"]:
from matching.im_models import aff_steerers
return aff_steerers.AffSteererMatcher(
device, max_num_keypoints, *args, **kwargs
)
elif matcher_name == "sift-nn":
from matching.im_models import handcrafted
return handcrafted.SiftNNMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "orb-nn":
from matching.im_models import handcrafted
return handcrafted.OrbNNMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "patch2pix":
from matching.im_models import matching_toolbox
return matching_toolbox.Patch2pixMatcher(device, *args, **kwargs)
elif matcher_name == "superglue":
from matching.im_models import matching_toolbox
return matching_toolbox.SuperGlueMatcher(
device, max_num_keypoints, *args, **kwargs
)
elif matcher_name == "r2d2":
from matching.im_models import matching_toolbox
return matching_toolbox.R2D2Matcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "d2net":
from matching.im_models import matching_toolbox
return matching_toolbox.D2netMatcher(device, *args, **kwargs)
elif matcher_name in ["duster", "dust3r"]:
from matching.im_models import duster
return duster.Dust3rMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name in ["master", "mast3r"]:
from matching.im_models import master
return master.Mast3rMatcher(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "doghardnet-nn":
from matching.im_models import matching_toolbox
return matching_toolbox.DogAffHardNNMatcher(
device, max_num_keypoints=max_num_keypoints, *args, **kwargs
)
elif "xfeat" in matcher_name:
if "steerers" in matcher_name:
from matching.im_models import xfeat_steerers
if kwargs.get("mode", None) is None:
# only use matcher_name to assign mode if mode is not a given kwarg
kwargs["mode"] = "semi-dense" if "star" in matcher_name else "sparse"
if kwargs.get("steerer_type", None) is None:
if "perm" in matcher_name:
kwargs["steerer_type"] = "perm"
else:
kwargs["steerer_type"] = (
"learned" # learned performs better, should be default
)
return xfeat_steerers.xFeatSteerersMatcher(
device, max_num_keypoints, *args, **kwargs
)
else:
from matching.im_models import xfeat
kwargs["mode"] = "semi-dense" if "star" in matcher_name else "sparse"
if matcher_name.removeprefix("xfeat").removeprefix("-") in [
"lg",
"lightglue",
"lighterglue",
]:
kwargs["mode"] = "lighterglue"
return xfeat.xFeatMatcher(
device, max_num_keypoints=max_num_keypoints, *args, **kwargs
)
elif matcher_name == "dedode-lg":
from matching.im_models import kornia
return kornia.DeDoDeLightGlue(device, *args, **kwargs)
elif matcher_name == "gim-dkm":
from matching.im_models import gim
return gim.GIM_DKM(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "gim-lg":
from matching.im_models import gim
return gim.GIM_LG(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "silk":
from matching.im_models import silk
return silk.SilkMatcher(device, *args, **kwargs)
elif matcher_name == "omniglue":
from matching.im_models import omniglue
return omniglue.OmniglueMatcher(device, *args, **kwargs)
elif matcher_name == "sift-sphereglue":
from matching.im_models import sphereglue
return sphereglue.SiftSphereGlue(device, max_num_keypoints, *args, **kwargs)
elif matcher_name == "superpoint-sphereglue":
from matching.im_models import sphereglue
return sphereglue.SuperpointSphereGlue(
device, max_num_keypoints, *args, **kwargs
)
elif "minima" in matcher_name:
from matching.im_models import minima
if "model_type" not in kwargs.keys():
if "lg" in matcher_name:
kwargs["model_type"] = "sp_lg"
elif "roma" in matcher_name:
kwargs["model_type"] = "roma"
if "tiny" in matcher_name:
kwargs["model_size"] = "tiny"
else:
kwargs["model_size"] = "large"
elif "loftr" in matcher_name:
kwargs["model_type"] = "loftr"
else: # set default to sp_lg
print("no model type set. Using sp-lg as default...")
kwargs["model_type"] = "sp_lg"
if kwargs["model_type"] == "sp_lg":
return minima.MINIMASpLgMatcher(device, *args, **kwargs)
if kwargs["model_type"] == "loftr":
return minima.MINIMALoFTRMatcher(device, *args, **kwargs)
if kwargs["model_type"] == "roma":
return minima.MINIMARomaMatcher(device, *args, **kwargs)
elif 'vggt' in matcher_name:
from matching.im_models.vggt import VGGTMatcher
return VGGTMatcher(device,max_num_keypoints,device, *args, **kwargs )
else:
raise RuntimeError(
f"Matcher {matcher_name} not yet supported. Consider submitted a PR to add it. Available models: {available_models}"
)
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