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#
# Copyright (C) 2023, Inria
# GRAPHDECO research group, https://team.inria.fr/graphdeco
# All rights reserved.
#
# This software is free for non-commercial, research and evaluation use
# under the terms of the LICENSE.md file.
#
# For inquiries contact george.drettakis@inria.fr
#
from scene.cameras import Camera
import numpy as np
from utils.general_utils import PILtoTorch
from utils.graphics_utils import fov2focal
WARNED = False
def loadCam(args, id, cam_info, resolution_scale):
image_rgb = PILtoTorch(cam_info.image).type("torch.ByteTensor")
background = PILtoTorch(cam_info.background)[:3, ...].type("torch.ByteTensor")
gt_image = image_rgb[:3, ...]
loaded_mask = None
return Camera(colmap_id=cam_info.uid, R=cam_info.R, T=cam_info.T,
FoVx=cam_info.FovX, FoVy=cam_info.FovY,
image=gt_image, gt_alpha_mask=loaded_mask, background=background, talking_dict=cam_info.talking_dict,
image_name=cam_info.image_name, uid=id, data_device=args.data_device)
def cameraList_from_camInfos(cam_infos, resolution_scale, args):
camera_list = []
for id, c in enumerate(cam_infos):
camera_list.append(loadCam(args, id, c, resolution_scale))
return camera_list
def camera_to_JSON(id, camera : Camera):
Rt = np.zeros((4, 4))
Rt[:3, :3] = camera.R.transpose()
Rt[:3, 3] = camera.T
Rt[3, 3] = 1.0
W2C = np.linalg.inv(Rt)
pos = W2C[:3, 3]
rot = W2C[:3, :3]
serializable_array_2d = [x.tolist() for x in rot]
camera_entry = {
'id' : id,
'img_name' : camera.image_name,
'width' : camera.width,
'height' : camera.height,
'position': pos.tolist(),
'rotation': serializable_array_2d,
'fy' : fov2focal(camera.FovY, camera.height),
'fx' : fov2focal(camera.FovX, camera.width)
}
return camera_entry
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