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import pickle
from pathlib import Path
import numpy as np
import poselib
import pycolmap
from siclib.models.extractor import VP
from .models.extractor import GeoCalib
from .utils.image import load_image
# flake8: noqa
# mypy: ignore-errors
class AbsolutePoseEstimator:
default_opts = {
"ransac": "poselib_gravity", # pycolmap, poselib, poselib_gravity
"refinement": "pycolmap_gravity", # pycolmap, pycolmap_gravity, none
"gravity_weight": 50000,
"max_reproj_error": 48.0,
"loss_function_scale": 1.0,
"use_vp": False,
"max_uncertainty": 10.0 / 180.0 * 3.1415, # radians
"cache_path": "../../outputs/inloc/calib.pickle",
}
def __init__(self, pose_opts=None):
pose_opts = {} if pose_opts is None else pose_opts
self.opts = {**self.default_opts, **pose_opts}
self.device = "cuda"
if self.opts["use_vp"]:
self.calib = VP().to(self.device)
self.cache_path = str(self.opts["cache_path"]).replace(".pickle", "_vp.pickle")
else:
self.calib = GeoCalib().to(self.device)
self.cache_path = str(self.opts["cache_path"])
# self.read_cache()
self.cache = {}
def read_cache(self):
print(f"Reading cache from {self.cache_path} ({Path(self.cache_path).exists()})")
if not Path(self.cache_path).exists():
self.cache = {}
return
with open(self.cache_path, "rb") as handle:
self.cache = pickle.load(handle)
def write_cache(self):
with open(self.cache_path, "wb") as handle:
pickle.dump(self.cache, handle, protocol=pickle.HIGHEST_PROTOCOL)
def __call__(self, query_path, p2d, p3d, camera_dict):
focal_length = pycolmap.Camera(camera_dict).mean_focal_length()
if query_path in self.cache:
calib = self.cache[query_path]
else:
calib = self.calib.calibrate(
load_image(query_path).to(self.device), priors={"f": focal_length}
)
calib = {k: v[0].detach().cpu().numpy() for k, v in calib.items()}
self.cache[query_path] = calib
# self.write_cache()
if self.opts["ransac"] == "pycolmap":
ret = pycolmap.absolute_pose_estimation(
p2d, p3d, camera_dict, self.opts["max_reproj_error"] # , do_refine=False
)
elif self.opts["ransac"] == "poselib":
M, ret = poselib.estimate_absolute_pose(
p2d,
p3d,
camera_dict,
ransac_opt={"max_reproj_error": self.opts["max_reproj_error"]},
)
ret["success"] = M is not None
ret["qvec"] = M.q
ret["tvec"] = M.t
elif self.opts["ransac"] == "poselib_gravity":
g_q = calib["gravity"].vec3d
g_qu = calib.get("gravity_uncertainty", self.opts["max_uncertainty"])
M, ret = poselib.estimate_absolute_pose_gravity(
p2d,
p3d,
camera_dict,
g_q,
g_qu * 2 * 180 / 3.1415, # convert to scalar
ransac_opt={"max_reproj_error": self.opts["max_reproj_error"]},
)
ret["success"] = M is not None
ret["qvec"] = M.q
ret["tvec"] = M.t
else:
raise NotImplementedError(self.opts["ransac"])
r_opts = {
"refine_focal_length": False,
"refine_extra_params": False,
"print_summary": False,
"loss_function_scale": self.opts["loss_function_scale"],
}
if self.opts["refinement"] == "pycolmap_gravity":
g_q = calib["gravity"].vec3d
g_qu = calib.get("gravity_uncertainty", self.opts["max_uncertainty"])
if g_qu <= self.opts["max_uncertainty"]:
g_gt = np.array([0, 0, 1]) # world frame
ret_ref = pycolmap.pose_refinement_gravity(
ret["tvec"],
ret["qvec"],
p2d,
p3d,
ret["inliers"],
camera_dict,
g_q,
g_gt,
self.opts["gravity_weight"],
r_opts,
)
else:
ret_ref = pycolmap.pose_refinement(
ret["tvec"],
ret["qvec"],
p2d,
p3d,
ret["inliers"],
camera_dict,
r_opts,
)
elif self.opts["refinement"] == "pycolmap":
ret_ref = pycolmap.pose_refinement(
ret["tvec"],
ret["qvec"],
p2d,
p3d,
ret["inliers"],
camera_dict,
r_opts,
)
elif self.opts["refinement"] == "none":
ret_ref = {}
else:
raise NotImplementedError(self.opts["refinement"])
ret = {**ret, **ret_ref}
ret["camera_dict"] = camera_dict
return ret, calib
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