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###
# Copyright (C) 2023, Computer Vision Lab, Seoul National University, https://cv.snu.ac.kr
# For permission requests, please contact robot0321@snu.ac.kr, esw0116@snu.ac.kr, namhj28@gmail.com, jarin.lee@gmail.com.
# All rights reserved.
###
import os
import random
from arguments import GSParams
from utils.system import searchForMaxIteration
from scene.dataset_readers import readDataInfo
from scene.gaussian_model import GaussianModel
class Scene:
gaussians: GaussianModel
def __init__(self, traindata, gaussians: GaussianModel, opt: GSParams):
self.traindata = traindata
self.gaussians = gaussians
info = readDataInfo(traindata, opt.white_background)
random.shuffle(info.train_cameras) # Multi-res consistent random shuffling
self.cameras_extent = info.nerf_normalization["radius"]
print("Loading Training Cameras")
self.train_cameras = info.train_cameras
print("Loading Preset Cameras")
self.preset_cameras = {}
for campath in info.preset_cameras.keys():
self.preset_cameras[campath] = info.preset_cameras[campath]
self.gaussians.create_from_pcd(info.point_cloud, self.cameras_extent)
self.gaussians.training_setup(opt)
def getTrainCameras(self):
return self.train_cameras
def getPresetCameras(self, preset):
assert preset in self.preset_cameras
return self.preset_cameras[preset] |