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Zero
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from pathlib import Path
import cv2
import numpy as np
import torch
import torch.nn.functional as F
from scenedino.common.cameras.fisheye import project_to_image
from scenedino.common.geometry import azimuth_elevation_to_rotation
class FisheyeToPinholeSampler:
def __init__(self, K_target, image_size_target) -> None:
self.K_target = K_target
self.image_size_target = image_size_target
x = (
torch.linspace(-1, 1, image_size_target[1])
.view(1, -1)
.expand(image_size_target)
)
y = (
torch.linspace(-1, 1, image_size_target[0])
.view(-1, 1)
.expand(image_size_target)
)
z = torch.ones_like(x)
xyz = torch.stack((x, y, z), dim=-1).view(-1, 3)
self.pts = (torch.inverse(torch.tensor(K_target)) @ xyz.T).T
def sample_pinhole(
self, img: torch.Tensor, calib, rotational_offset: torch.Tensor
) -> torch.Tensor:
xyz_pinhole = (rotational_offset @ self.pts.T).T
xy, _ = project_to_image(xyz_pinhole, calib)
img = img.unsqueeze(0)
resampled_img = F.grid_sample(
img, xy.view(1, *self.image_size_target, 2), align_corners=True
).squeeze(0)
return resampled_img
def load_image(path: Path) -> torch.Tensor:
return torch.from_numpy(
cv2.cvtColor(
cv2.imread(str(path)),
cv2.COLOR_BGR2RGB,
).astype(np.float32)
/ 255
)
def load_fisheye_image_as_pinhole(
path: Path,
resampler: FisheyeToPinholeSampler,
calib,
azimuth: float,
elevation: float,
) -> tuple[torch.Tensor, torch.Tensor]:
img = load_image(path)
rotational_offset = azimuth_elevation_to_rotation(azimuth, elevation)
return resampler.sample_pinhole(img, calib, rotational_offset), rotational_offset
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