Trikang
[3D Gaussian Splatting 코드 분석] train.py - Scene 로딩 본문
train.py의 main 함수 전체 구조
if __name__ == "__main__":
# Set up command line argument parser
parser = ArgumentParser(description="Training script parameters")
lp = ModelParams(parser)
op = OptimizationParams(parser)
pp = PipelineParams(parser)
parser.add_argument('--ip', type=str, default="127.0.0.1")
parser.add_argument('--port', type=int, default=6009)
parser.add_argument('--debug_from', type=int, default=-1)
parser.add_argument('--detect_anomaly', action='store_true', default=False)
parser.add_argument("--test_iterations", nargs="+", type=int, default=[7_000, 30_000])
parser.add_argument("--save_iterations", nargs="+", type=int, default=[7_000, 30_000])
parser.add_argument("--quiet", action="store_true")
parser.add_argument("--checkpoint_iterations", nargs="+", type=int, default=[])
parser.add_argument("--start_checkpoint", type=str, default = None)
args = parser.parse_args(sys.argv[1:])
args.save_iterations.append(args.iterations)
print("Optimizing " + args.model_path)
# Initialize system state (RNG)
safe_state(args.quiet)
# Start GUI server, configure and run training
network_gui.init(args.ip, args.port)
torch.autograd.set_detect_anomaly(args.detect_anomaly)
training(lp.extract(args), op.extract(args), pp.extract(args), args.test_iterations, args.save_iterations, args.checkpoint_iterations, args.start_checkpoint, args.debug_from)
# All done
print("\nTraining complete.")
main 함수 실행 시, ArgumentParser, ModelParams, OptimizationParams, PipelineParams 네 개의 인자를 받아옴
parser = ArgumentParser(description="Training script parameters")
lp = ModelParams(parser)
op = OptimizationParams(parser)
pp = PipelineParams(parser)class ModelParams(ParamGroup):
def __init__(self, parser, sentinel=False):
self.sh_degree = 3
self._source_path = ""
self._model_path = ""
self._images = "images"
self._resolution = -1
self._white_background = False
self.data_device = "cuda"
self.eval = False
super().__init__(parser, "Loading Parameters", sentinel)class OptimizationParams(ParamGroup):
def __init__(self, parser):
self.iterations = 30_000
self.position_lr_init = 0.00016
self.position_lr_final = 0.0000016
self.position_lr_delay_mult = 0.01
self.position_lr_max_steps = 30_000
self.feature_lr = 0.0025
self.opacity_lr = 0.05
self.scaling_lr = 0.005
self.rotation_lr = 0.001
self.percent_dense = 0.01
self.lambda_dssim = 0.2
self.densification_interval = 100
self.opacity_reset_interval = 3000
self.densify_from_iter = 500
self.densify_until_iter = 15_000
self.densify_grad_threshold = 0.0002
self.random_background = False
super().__init__(parser, "Optimization Parameters")class PipelineParams(ParamGroup):
def __init__(self, parser):
self.convert_SHs_python = False
self.compute_cov3D_python = False
self.debug = False
super().__init__(parser, "Pipeline Parameters")
그 이후에 GaussianModel을 로드하게 되는데, 로드 당시 GaussianModel의 멤버 변수의 상태를 확인해보면 아래와 같음.
'active_sh_degree': 0,
'max_sh_degree': 3,
'_xyz': tensor([]),
'_features_dc': tensor([]),
'_features_rest': tensor([]),
'_scaling': tensor([]),
'_rotation': tensor([]),
'_opacity': tensor([]),
'max_radii2D': tensor([]),
'xyz_gradient_accum': tensor([]),
'denom': tensor([]),
'optimizer': None,
'percent_dense': 0,
'spatial_lr_scale': 0,
'scaling_activation': <built-in method exp of type object at 0x7f75733bb140>,
'scaling_inverse_activation': <built-in method log of type object at 0x7f75733bb140>,
'covariance_activation': <function GaussianModel.setup_functions.<locals>.build_covariance_from_scaling_rotation at 0x7f751c3fac20>,
'opacity_activation': <built-in method sigmoid of type object at 0x7f75733bb140>,
'inverse_opacity_activation': <function inverse_sigmoid at 0x7f751ce820e0>,
'rotation_activation': <function normalize at 0x7f751e1ec170>
그 이후에 Scene 인스턴스를 생성하는데, 이때 아래와 같은 로그가 발생
scene = Scene(dataset, gaussians)
#####
Reading camera 1/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 2/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 3/77intr.model: PINHOLE [07/04 10:57:51]
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Reading camera 56/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 57/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 58/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 59/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 60/77intr.model: PINHOLE [07/04 10:57:51]
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Reading camera 73/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 74/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 75/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 76/77intr.model: PINHOLE [07/04 10:57:51]
Reading camera 77/77intr.model: PINHOLE [07/04 10:57:51]
[07/04 10:57:51]
Loading Training Cameras [07/04 10:57:51]
Loading Test Cameras [07/04 10:58:13]
Number of points at initialisation : 41332 [07/04 10:58:16]
{'model_path': 'output/odm_aukerman', 'loaded_iter': None, 'gaussians': <scene.gaussian_model.GaussianModel object at 0x7f70a3bff7d0>, 'train_cameras': {1.0: [Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera()]}, 'test_cameras': {1.0: [Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera(), Camera()]}, 'cameras_extent': 7.581940841674805} [07/04 10:58:16]
self.loaded_iter에는 아래와 같이 None 값이 담긴다.
if load_iteration:
if load_iteration == -1:
self.loaded_iter = searchForMaxIteration(os.path.join(self.model_path, "point_cloud"))
else:
self.loaded_iter = load_iteration
print("Loading trained model at iteration {}".format(self.loaded_iter))
######################################################
self.loaded_iter [07/04 11:15:26]
None [07/04 11:15:26]
scene_info를 저장한 이후의 코드에는 아래와 같은 값이 출력된다.
scene_info는 scene.dataset_readers.SceneInfo 타입의 인스턴스이다.
self.train_cameras = {}
self.test_cameras = {}
if os.path.exists(os.path.join(args.source_path, "sparse")):
scene_info = sceneLoadTypeCallbacks["Colmap"](args.source_path, args.images, args.eval)
elif os.path.exists(os.path.join(args.source_path, "transforms_train.json")):
print("Found transforms_train.json file, assuming Blender data set!")
scene_info = sceneLoadTypeCallbacks["Blender"](args.source_path, args.white_background, args.eval)
else:
assert False, "Could not recognize scene type!"
print('scene_info')
print(scene_info)
################################################
SceneInfo(point_cloud=BasicPointCloud(points=array([[-3.1786976, 1.1268233, 4.1232734],
[-1.3131675, 0.859263 , 4.158581 ],
[-1.0692643, 1.0911088, 4.0958204],
...,
[ 1.2832712, -1.4758004, 4.7903233],
[-3.0944202, -1.4772788, 4.8030815],
[-3.0393033, -2.4001055, 5.0467534]], dtype=float32), colors=array([[0.59607843, 0.62745098, 0.36470588],
[0.71764706, 0.74117647, 0.50588235],
[0.61960784, 0.64705882, 0.38431373],
...,
[0.60784314, 0.61176471, 0.43921569],
[0.42745098, 0.54901961, 0.23529412],
[0. , 0. , 0. ]]), normals=array([[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.],
...,
[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.]], dtype=float32)), train_cameras=[CameraInfo(uid=1, R=array([[ 0.32542384, -0.9333629 , -0.15143654],
[ 0.94505887, 0.31579403, 0.08448592],
[-0.03103327, -0.17061017, 0.98484979]]), T=array([-5.62433605, 0.23668308, 1.21057039]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E150>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00230.JPG', image_name='DSC00230', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.98462343, -0.11413734, -0.13224739],
[ 0.14339416, 0.96045088, 0.23868854],
[ 0.09977384, -0.25398184, 0.96204907]]), T=array([-4.18595828, -1.42684032, 0.5656123 ]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784F90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00232.JPG', image_name='DSC00232', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.98125486, 0.16857012, 0.09339706],
[-0.18138667, 0.97157419, 0.15212651],
[-0.06509819, -0.16621586, 0.98393827]]), T=array([-3.52956981, -0.72790771, -0.21369828]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E090>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00233.JPG', image_name='DSC00233', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.96972867, 0.21275549, 0.11983912],
[-0.23374937, 0.95074414, 0.20358489],
[-0.07062254, -0.22543442, 0.97169531]]), T=array([-2.93262951, 0.86845088, -0.34200852]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E210>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00234.JPG', image_name='DSC00234', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.98456112, -0.14809608, -0.09331107],
[ 0.16581766, 0.95986912, 0.22617642],
[ 0.05607057, -0.23815713, 0.96960676]]), T=array([-1.61471343, 3.45824471, 0.23501635]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E390>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00235.JPG', image_name='DSC00235', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99688478, 0.01230462, 0.07790586],
[-0.03333559, 0.96092561, 0.27479212],
[-0.07148053, -0.27653312, 0.9583423 ]]), T=array([-1.74922839, 4.90563595, 0.13722734]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E2D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00236.JPG', image_name='DSC00236', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.27473496, 0.96122977, 0.02362275],
[-0.88969094, -0.26345186, 0.3728849 ],
[ 0.36465152, 0.08142757, 0.92757685]]), T=array([-6.02848676, 0.89750568, 0.79862506]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E450>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00237.JPG', image_name='DSC00237', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.73217654, -0.68092754, 0.01597502],
[ 0.64993145, -0.69144763, 0.31541921],
[-0.20373173, 0.24132521, 0.94881796]]), T=array([-2.5937141 , -1.86538487, 0.05196471]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E510>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00239.JPG', image_name='DSC00239', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.68863241, -0.72447952, 0.03024618],
[ 0.68020891, -0.63097692, 0.37307367],
[-0.25119959, 0.27748434, 0.92730858]]), T=array([-3.1723651 , -0.1409423 , -0.17426174]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E690>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00240.JPG', image_name='DSC00240', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.77339386, -0.63280795, 0.03763022],
[ 0.62832877, -0.75734298, 0.17786109],
[-0.08405293, 0.16120082, 0.98333585]]), T=array([-3.72541644, 2.12336803, 0.36340504]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E810>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00241.JPG', image_name='DSC00241', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.53363851, -0.84456252, -0.04409194],
[ 0.82992965, 0.51294198, 0.21933377],
[-0.16262448, -0.15363815, 0.97465306]]), T=array([-4.42720892, -1.75482 , 0.11212468]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E750>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00242.JPG', image_name='DSC00242', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.40493299, -0.91423255, 0.0144261 ],
[ 0.86498597, 0.38813909, 0.31803667],
[-0.29635881, -0.11630517, 0.94796865]]), T=array([-4.7177552 , 0.63675719, -0.52287064]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784E10>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00243.JPG', image_name='DSC00243', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.9573479 , 0.25859648, -0.1288909 ],
[-0.2269965 , 0.94913116, 0.21822608],
[ 0.17876687, -0.1796605 , 0.96734922]]), T=array([-2.27695949, -1.75543799, 0.29648052]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784C90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00244.JPG', image_name='DSC00244', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.86951193, 0.31505748, 0.38037848],
[-0.39739714, 0.90359138, 0.15999415],
[-0.29329936, -0.29027815, 0.91088643]]), T=array([-2.02557647, 1.64661627, -0.69890664]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784D50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00246.JPG', image_name='DSC00246', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.93152508, -0.36366027, -0.00349647],
[ 0.35449611, -0.91011355, 0.21453632],
[-0.08120052, 0.19860648, 0.97670975]]), T=array([-2.20579846, 0.82017299, 0.13557286]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784A50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00249.JPG', image_name='DSC00249', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99860205, 0.03962147, 0.03498693],
[-0.04532264, 0.98243157, 0.18103608],
[-0.02719935, -0.1823687 , 0.98285393]]), T=array([-1.72504717, -0.7269751 , -0.18964444]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784B10>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00251.JPG', image_name='DSC00251', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.95740065, -0.21964006, -0.18746265],
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[-0.22600116, 0.3468361 , 0.91029017]]), T=array([-2.4577792 , 0.09648264, -0.22584941]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0A40E10>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00293.JPG', image_name='DSC00293', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.85809178, -0.48217086, 0.17660626],
[ 0.51332386, -0.81438768, 0.27068677],
[ 0.01330869, 0.3229303 , 0.94632917]]), T=array([-2.4179182 , 2.58584229, -0.03783915]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0A40ED0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00294.JPG', image_name='DSC00294', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.9201835 , 0.38197543, 0.08577353],
[-0.38301229, 0.92373141, -0.00467638],
[-0.08101796, -0.02854919, 0.99630369]]), T=array([-1.39639593, -1.14872302, -0.13728855]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784210>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00295.JPG', image_name='DSC00295', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.96777355, 0.06930505, -0.24209743],
[-0.03555996, 0.9893602 , 0.14107406],
[ 0.24929871, -0.12791877, 0.95994111]]), T=array([-0.97904401, 0.99733057, 0.11069444]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784150>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00296.JPG', image_name='DSC00296', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.95823446, 0.27479614, 0.07920737],
[-0.2796856 , 0.95827678, 0.05900485],
[-0.05968828, -0.07869364, 0.99511036]]), T=array([-1.03236379, 2.56830748, -0.47777556]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765F90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00297.JPG', image_name='DSC00297', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.67122653, -0.70347555, 0.23361741],
[ 0.74095172, -0.64573434, 0.18443889],
[ 0.02110653, 0.2968995 , 0.95467544]]), T=array([-0.84635264, -2.02577915, 0.45314018]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765B50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00298.JPG', image_name='DSC00298', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.78100964, -0.61980642, 0.07657639],
[ 0.61107324, -0.73312159, 0.29853346],
[-0.12889315, 0.2799513 , 0.95132215]]), T=array([-1.72476434, 1.69301623, -0.13280909]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765E10>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00300.JPG', image_name='DSC00300', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.73626277, -0.65266527, 0.17873215],
[ 0.66547525, -0.65044338, 0.36615039],
[-0.12271849, 0.38852472, 0.91322982]]), T=array([-2.29423683, 3.32215249, -0.73963194]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765D50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00301.JPG', image_name='DSC00301', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.9609026 , 0.15821016, -0.22723497],
[-0.10273575, 0.9658155 , 0.23800375],
[ 0.25712167, -0.20535326, 0.94430847]]), T=array([-1.24457933, -3.22480803, 0.32232812]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765C90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00302.JPG', image_name='DSC00302', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.97567389, 0.20328051, -0.08208222],
[-0.1901333 , 0.97102643, 0.14476533],
[ 0.10913198, -0.12563719, 0.98605553]]), T=array([-0.94858708, -1.45151812, 0.19260704]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765BD0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00303.JPG', image_name='DSC00303', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.96775162, 0.25178039, 0.0079642 ],
[-0.25187063, 0.9665986 , 0.04741654],
[ 0.00424037, -0.04789338, 0.99884345]]), T=array([-0.3713071 , 0.30787531, -0.01970285]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765A90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00304.JPG', image_name='DSC00304', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99374807, -0.02036419, -0.10977278],
[ 0.02979357, 0.9959392 , 0.08495556],
[ 0.10759697, -0.08769494, 0.99031939]]), T=array([ 0.50079283, 1.93021076, -0.33138593]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0795F50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00305.JPG', image_name='DSC00305', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.3262383 , -0.94388687, 0.05144072],
[ 0.90665875, -0.29704559, 0.29955604],
[-0.26746678, 0.14436583, 0.95269094]]), T=array([-0.33817873, -1.71396935, 0.04532109]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C07659D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00306.JPG', image_name='DSC00306', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.22168184, 0.97511649, 0.00223273],
[-0.94046509, 0.21319812, 0.26471111],
[ 0.25764816, -0.06078145, 0.96432517]]), T=array([-0.40413116, 1.07180826, -0.09120542]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765810>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00308.JPG', image_name='DSC00308', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99861644, 0.0490227 , 0.01902588],
[-0.05142253, 0.9860411 , 0.15836245],
[-0.01099695, -0.1591217 , 0.98719773]]), T=array([ 1.10543389, 0.61574127, -0.08844957]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765750>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00309.JPG', image_name='DSC00309', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99399845, 0.05917031, 0.09201067],
[-0.07806429, 0.97289188, 0.21768639],
[-0.07663586, -0.22356268, 0.9716721 ]]), T=array([1.69329046, 2.20309806, 0.09623421]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0795250>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00310.JPG', image_name='DSC00310', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99711715, 0.07032624, -0.02848873],
[-0.06284341, 0.97582249, 0.20933506],
[ 0.04252169, -0.20694125, 0.97742888]]), T=array([ 1.8505824 , 3.99751673, -0.16068789]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C015A850>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00311.JPG', image_name='DSC00311', width=4863, height=3651)], test_cameras=[CameraInfo(uid=1, R=array([[ 0.30867647, -0.94442357, -0.11306172],
[ 0.94417696, 0.28985136, 0.15657604],
[-0.11510301, -0.15508161, 0.98117327]]), T=array([-5.80128379, -1.31484576, 0.68506489]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784ED0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00229.JPG', image_name='DSC00229', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.81338948, -0.573708 , 0.09621168],
[ 0.58127693, -0.80802736, 0.09596311],
[ 0.02268687, 0.13398101, 0.99072418]]), T=array([-2.23359615, -3.81911192, 0.11599525]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076E5D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00238.JPG', image_name='DSC00238', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.9059789 , -0.40026793, -0.13779629],
[ 0.41659773, 0.9008201 , 0.12234979],
[ 0.07515697, -0.16825195, 0.98287472]]), T=array([ 0.83418685, 3.94336251, -0.23429936]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784BD0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00247.JPG', image_name='DSC00247', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.69864554, -0.71546088, 0.00318527],
[ 0.68484415, -0.66744657, 0.29240992],
[-0.20708186, 0.2064723 , 0.95628777]]), T=array([-2.35238125, 3.1316468 , -0.30145861]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C07845D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00257.JPG', image_name='DSC00257', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99710656, -0.05761499, 0.04958844],
[ 0.05272897, 0.99410302, 0.09475671],
[-0.05475543, -0.09186779, 0.99426463]]), T=array([ 2.62246121, 4.49152461, -0.4059775 ]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C076EA50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00267.JPG', image_name='DSC00267', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99473871, 0.10227251, 0.00593505],
[-0.10103762, 0.96986078, 0.22172386],
[ 0.01692008, -0.22115697, 0.97509143]]), T=array([-2.13486113, 4.39460576, -0.2452242 ]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0A40090>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00275.JPG', image_name='DSC00275', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.78642813, -0.61761495, 0.00908721],
[ 0.578305 , -0.73104545, 0.36212688],
[-0.21701181, 0.29004194, 0.93208452]]), T=array([-3.79418612, 2.42648612, -0.64504363]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0A40750>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00283.JPG', image_name='DSC00283', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.69239314, -0.71511126, 0.09595641],
[ 0.71952263, -0.67445268, 0.16553176],
[-0.05365556, 0.18365586, 0.98152514]]), T=array([-0.78498243, -3.42478178, 0.05017422]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0784090>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00291.JPG', image_name='DSC00291', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.55198023, -0.82922661, 0.08775562],
[ 0.79123192, -0.48763816, 0.3690001 ],
[-0.26319172, 0.27311581, 0.92527719]]), T=array([-1.41048914, -0.59628944, -0.02591331]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765ED0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00299.JPG', image_name='DSC00299', width=4863, height=3651), CameraInfo(uid=1, R=array([[-1.44128674e-01, -9.89558948e-01, -1.14333368e-04],
[ 9.30960506e-01, -1.35633013e-01, 3.38992952e-01],
[-3.35469017e-01, 4.87521650e-02, 9.40788906e-01]]), T=array([-0.9918353 , -0.35863956, -0.15710331]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7FA2C0765910>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00307.JPG', image_name='DSC00307', width=4863, height=3651)], nerf_normalization={'translate': array([-0.16077894, -0.07594691, -0.01542493], dtype=float32), 'radius': 7.581940841674805}, ply_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/sparse/0/points3D.ply') [07/04 11:15:27]
SceneInfo는 named tuple이므로 asdict()를 이용하여 아래처럼 확인할 수 있음
{'model_path': 'output/odm_aukerman', 'loaded_iter': None, 'gaussians': <scene.gaussian_model.GaussianModel object at 0x7f243187f450>, 'train_cameras': {}, 'test_cameras': {}}
# --------------------------------------------------------------------
OrderedDict([('point_cloud', BasicPointCloud(points=array([[-3.1786976, 1.1268233, 4.1232734],
[-1.3131675, 0.859263 , 4.158581 ],
[-1.0692643, 1.0911088, 4.0958204],
...,
[ 1.2832712, -1.4758004, 4.7903233],
[-3.0944202, -1.4772788, 4.8030815],
[-3.0393033, -2.4001055, 5.0467534]], dtype=float32), colors=array([[0.59607843, 0.62745098, 0.36470588],
[0.71764706, 0.74117647, 0.50588235],
[0.61960784, 0.64705882, 0.38431373],
...,
[0.60784314, 0.61176471, 0.43921569],
[0.42745098, 0.54901961, 0.23529412],
[0. , 0. , 0. ]]), normals=array([[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.],
...,
[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.]], dtype=float32))), ('train_cameras', [CameraInfo(uid=1, R=array([[ 0.32542384, -0.9333629 , -0.15143654],
[ 0.94505887, 0.31579403, 0.08448592],
[-0.03103327, -0.17061017, 0.98484979]]), T=array([-5.62433605, 0.23668308, 1.21057039]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9E90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00230.JPG', image_name='DSC00230', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.98462343, -0.11413734, -0.13224739],
[ 0.14339416, 0.96045088, 0.23868854],
[ 0.09977384, -0.25398184, 0.96204907]]), T=array([-4.18595828, -1.42684032, 0.5656123 ]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9D10>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00232.JPG', image_name='DSC00232', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.98125486, 0.16857012, 0.09339706],
[-0.18138667, 0.97157419, 0.15212651],
[-0.06509819, -0.16621586, 0.98393827]]), T=array([-3.52956981, -0.72790771, -0.21369828]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9DD0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00233.JPG', image_name='DSC00233', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.96972867, 0.21275549, 0.11983912],
[-0.23374937, 0.95074414, 0.20358489],
[-0.07062254, -0.22543442, 0.97169531]]), T=array([-2.93262951, 0.86845088, -0.34200852]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9F50>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00234.JPG', image_name='DSC00234', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.98456112, -0.14809608, -0.09331107],
[ 0.16581766, 0.95986912, 0.22617642],
[ 0.05607057, -0.23815713, 0.96960676]]), T=array([-1.61471343, 3.45824471, 0.23501635]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB6110>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00235.JPG', image_name='DSC00235', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99688478, 0.01230462, 0.07790586],
[-0.03333559, 0.96092561, 0.27479212],
[-0.07148053, -0.27653312, 0.9583423 ]]), T=array([-1.74922839, 4.90563595, 0.13722734]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB6050>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00236.JPG', image_name='DSC00236', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.27473496, 0.96122977, 0.02362275],
[-0.88969094, -0.26345186, 0.3728849 ],
[ 0.36465152, 0.08142757, 0.92757685]]), T=array([-6.02848676, 0.89750568, 0.79862506]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB61D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00237.JPG', image_name='DSC00237', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.73217654, -0.68092754, 0.01597502],
[ 0.64993145, -0.69144763, 0.31541921],
[-0.20373173, 0.24132521, 0.94881796]]), T=array([-2.5937141 , -1.86538487, 0.05196471]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB6290>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00239.JPG', image_name='DSC00239', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.68863241, -0.72447952, 0.03024618],
[ 0.68020891, -0.63097692, 0.37307367],
[-0.25119959, 0.27748434, 0.92730858]]), T=array([-3.1723651 , -0.1409423 , -0.17426174]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB6410>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00240.JPG', image_name='DSC00240', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.77339386, -0.63280795, 0.03763022],
[ 0.62832877, -0.75734298, 0.17786109],
[-0.08405293, 0.16120082, 0.98333585]]), T=array([-3.72541644, 2.12336803, 0.36340504]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB6590>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00241.JPG', image_name='DSC00241', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.53363851, -0.84456252, -0.04409194],
[ 0.82992965, 0.51294198, 0.21933377],
[-0.16262448, -0.15363815, 0.97465306]]), T=array([-4.42720892, -1.75482 , 0.11212468]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774DFB64D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00242.JPG', image_name='DSC00242', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.40493299, -0.91423255, 0.0144261 ],
[ 0.86498597, 0.38813909, 0.31803667],
[-0.29635881, -0.11630517, 0.94796865]]), T=array([-4.7177552 , 0.63675719, -0.52287064]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9B90>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00243.JPG', image_name='DSC00243', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.9573479 , 0.25859648, -0.1288909 ],
[-0.2269965 , 0.94913116, 0.21822608],
[ 0.17876687, -0.1796605 , 0.96734922]]), T=array([-2.27695949, -1.75543799, 0.29648052]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9A10>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00244.JPG', image_name='DSC00244', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.86951193, 0.31505748, 0.38037848],
[-0.39739714, 0.90359138, 0.15999415],
[-0.29329936, -0.29027815, 0.91088643]]), T=array([-2.02557647, 1.64661627, -0.69890664]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9AD0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00246.JPG', image_name='DSC00246', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.93152508, -0.36366027, -0.00349647],
[ 0.35449611, -0.91011355, 0.21453632],
[-0.08120052, 0.19860648, 0.97670975]]), T=array([-2.20579846, 0.82017299, 0.13557286]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C97D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00249.JPG', image_name='DSC00249', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99860205, 0.03962147, 0.03498693],
[-0.04532264, 0.98243157, 0.18103608],
[-0.02719935, -0.1823687 , 0.98285393]]), T=array([-1.72504717, -0.7269751 , -0.18964444]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9890>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00251.JPG', image_name='DSC00251', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.95740065, -0.21964006, -0.18746265],
[ 0.25740167, 0.94336552, 0.20929855],
[ 0.13087545, -0.24863577, 0.95971447]]), T=array([-0.74720041, 1.10822204, 0.05595364]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9710>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00252.JPG', image_name='DSC00252', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99797278, -0.03322084, 0.05428349],
[ 0.01733131, 0.96257577, 0.27045796],
[-0.06123682, -0.26896888, 0.96120018]]), T=array([-0.40914667, 2.7405791 , -0.08681369]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9650>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00253.JPG', image_name='DSC00253', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.56316119, -0.82633518, 0.00443323],
[ 0.7820127 , -0.53120571, 0.32600096],
[-0.2670311 , 0.18705793, 0.94535904]]), T=array([-0.58443205, -2.23156534, -0.01266134]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9590>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00254.JPG', image_name='DSC00254', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.62738846, -0.77325082, 0.09201566],
[ 0.77399634, -0.60624776, 0.18273836],
[-0.0855183 , 0.18586772, 0.97884616]]), T=array([-1.36974544, -0.55007238, 0.11282753]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C9410>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00255.JPG', image_name='DSC00255', width=4863, height=3651), CameraInfo(uid=1, R=array([[-0.54765454, -0.83571714, -0.04063692],
[ 0.78964861, -0.53230271, 0.3051375 ],
[-0.27663978, 0.13502105, 0.95144088]]), T=array([-2.13319753, 0.88204502, -0.23605275]), FovY=0.9384727420170449, FovX=1.1887788848677407, image=<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=4863x3651 at 0x7F774D6C94D0>, image_path='/home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/images/DSC00256.JPG', image_name='DSC00256', width=4863, height=3651), CameraInfo(uid=1, R=array([[ 0.99219897, 0.06373022, -0.1071432 ],
[-0.02754129, 0.95027535, 0.31019065],
[ 0.12158406, -0.30481998, 0.94461743]]), T=array([-1.34513483, -2.76877453, -0.00527228]), Fov
그 후 코드 진행은 다음과 같다(적당히 주석 처리)
if not self.loaded_iter:
print(f'scene_info.ply_path: {scene_info.ply_path}')
print(f'self.model_path: {self.model_path}')
print(f'scene_info.test_cameras: {scene_info.test_cameras}')
print(f'scene_info.train_cameras: {scene_info.train_cameras}')
print(f'scene_info.nerf_normalization: {scene_info.nerf_normalization}')
print(f'scene_info.point_cloud: {scene_info.point_cloud}')
# scene_info.ply_path에 있는 파일의 내용을 self.model_path에 있는 폴더에 input.ply로 저장
# 우리 예시에서는
"""
scene_info.ply_path: /home/user/3D_survey/models/gaussian-splatting/data/odm_aukerman/sparse/0/points3D.ply [07/04 13:56:34]
self.model_path: output/odm_aukerman [07/04 13:56:34]
"""
with open(scene_info.ply_path, 'rb') as src_file, open(os.path.join(self.model_path, "input.ply") , 'wb') as dest_file:
dest_file.write(src_file.read())
json_cams = []
camlist = []
if scene_info.test_cameras:
camlist.extend(scene_info.test_cameras)
print(f'scene_info.test_cameras: {scene_info.test_cameras}')
print(f'len - scene_info.test_cameras: {len(scene_info.test_cameras)}')
if scene_info.train_cameras:
camlist.extend(scene_info.train_cameras)
for id, cam in enumerate(camlist):
json_cams.append(camera_to_JSON(id, cam))
with open(os.path.join(self.model_path, "cameras.json"), 'w') as file:
json.dump(json_cams, file)
"""
shuffle: 카메라 리스트를 섞을지 여부
"""
if shuffle:
random.shuffle(scene_info.train_cameras) # Multi-res consistent random shuffling
random.shuffle(scene_info.test_cameras) # Multi-res consistent random shuffling
# 역할: 카메라 리스트의 최대 거리를 저장
self.cameras_extent = scene_info.nerf_normalization["radius"]
print(f'self.cameras_extent: {self.cameras_extent}')
print(f'scene_info.nerf_normalization: {scene_info.nerf_normalization}')
# print(f'scene_info.point_cloud: {scene_info.point_cloud.}')
print(f'scene_info.point_cloud: {scene_info.point_cloud.points}')
print(f'len - scene_info.point_cloud: {len(scene_info.point_cloud.points)}')
for resolution_scale in resolution_scales:
print("Loading Training Cameras")
self.train_cameras[resolution_scale] = cameraList_from_camInfos(scene_info.train_cameras, resolution_scale, args)
print("Loading Test Cameras")
self.test_cameras[resolution_scale] = cameraList_from_camInfos(scene_info.test_cameras, resolution_scale, args)
print(f'self.train_cameras: {self.train_cameras}')
print(f'self.test_cameras: {self.test_cameras}')
if self.loaded_iter:
# self.model_path/point_cloud/iteration_{self.loaded_iter}/point_cloud.ply 파일을 로드
self.gaussians.load_ply(os.path.join(self.model_path,
"point_cloud",
"iteration_" + str(self.loaded_iter),
"point_cloud.ply"))
else:
# scene_info.point_cloud를 이용하여 GaussianModel을 생성
self.gaussians.create_from_pcd(scene_info.point_cloud, self.cameras_extent)
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