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import sys
import os
import numpy as np
import open3d as o3d
import torch
from mmengine import Config
from pyvirtualdisplay import Display
from tqdm import tqdm
sys.path.append("Metric3D")
def display_wrapper(func):
def inner(*args, **kwargs):
with Display(visible=False, size=(1920, 1080)):
return func(*args, **kwargs)
return inner
def relative_pose(rt: np.ndarray, mode: str, ref_index: int = 0) -> np.ndarray:
if mode == "left":
rt = np.linalg.inv(rt[ref_index]) @ rt
elif mode == "right":
rt = rt @ np.linalg.inv(rt[ref_index])
return rt
def project_point_cloud(
frame: np.ndarray,
depth: np.ndarray,
intrinsics: list[float],
remove_outliers: bool = True,
voxel_size: float = None,
) -> o3d.geometry.PointCloud:
from mono.utils.unproj_pcd import reconstruct_pcd
points = reconstruct_pcd(depth, *intrinsics).reshape(-1, 3)
colors = frame.reshape(-1, 3) / 255
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(points.astype(np.double))
pcd.colors = o3d.utility.Vector3dVector(colors.astype(np.double))
if remove_outliers:
cl, ind = pcd.remove_statistical_outlier(nb_neighbors=12, std_ratio=3.0)
pcd = pcd.select_by_index(ind)
if voxel_size is not None:
pcd = pcd.voxel_down_sample(voxel_size=0.5)
return pcd
def create_camera_frustum(
frame: np.ndarray,
intrinsic: o3d.camera.PinholeCameraIntrinsic,
c2w: np.ndarray,
frustum_scale: float = 0.5,
):
W, H = intrinsic.width, intrinsic.height
fx, fy = intrinsic.get_focal_length()
cx, cy = intrinsic.get_principal_point()
z = frustum_scale
x = (W - cx) * z / fx
y = (H - cy) * z / fy
points = [[0, 0, 0], [-x, -y, z], [x, -y, z], [x, y, z], [-x, y, z]]
lines = [[0, 1], [0, 2], [0, 3], [0, 4], [1, 2], [2, 3], [3, 4], [4, 1]]
line_set = o3d.geometry.LineSet(
points=o3d.utility.Vector3dVector(points),
lines=o3d.utility.Vector2iVector(lines),
)
line_set.paint_uniform_color([0.8, 0.2, 0.2])
line_set.transform(c2w)
vertices = [points[i] for i in [1, 2, 3, 4]]
triangles = [[0, 1, 2], [0, 2, 3]]
img_plane = o3d.geometry.TriangleMesh(
vertices=o3d.utility.Vector3dVector(vertices),
triangles=o3d.utility.Vector3iVector(triangles),
)
img_plane.triangle_uvs = o3d.utility.Vector2dVector(
np.array([[0, 1], [1, 1], [1, 0], [0, 1], [1, 0], [0, 0]])
)
img_plane.transform(c2w)
material = o3d.visualization.rendering.MaterialRecord()
material.shader = "defaultUnlit"
material.albedo_img = o3d.geometry.Image(frame)
return line_set, img_plane, material
class Previewer:
def __init__(self, model_path: str = "pretrained/metric_depth_vit_large_800k.pth"):
self.model_path = model_path
self.depth_predictor = None
def init_depth_predictor(self):
from mono.model.monodepth_model import get_configured_monodepth_model
from mono.utils.running import load_ckpt
self.config = Config.fromfile(
"Metric3D/mono/configs/HourglassDecoder/vit.raft5.large.py"
)
model = get_configured_monodepth_model(self.config)
model = torch.nn.DataParallel(model).cuda().eval().requires_grad_(False)
model, _, _, _ = load_ckpt(self.model_path, model, strict_match=False)
self.depth_predictor = model
def estimate_depths(
self, frames: np.ndarray, intrinsics: list[float]
) -> np.ndarray:
"""
:param frames: `np.ndarray` of shape (B, H, W, C) and range (0, 255)
:param intrinsics: list of [fx, fy, cx, cy]
:return depths: `np.ndarray` of shape (B, H, W) and range (0, 300)
"""
from mono.utils.do_test import transform_test_data_scalecano
if self.depth_predictor is None:
self.init_depth_predictor()
B, H, W, C = frames.shape
rgb_inputs, pads = [], []
for frame in frames:
rgb_input, _, pad, label_scale_factor = transform_test_data_scalecano(
frame, intrinsics, self.config.data_basic
)
rgb_inputs.append(rgb_input)
pads.append(pad)
with torch.inference_mode(), torch.autocast("cuda"): # b c h w
depths, _, _ = self.depth_predictor.module.inference(
{"input": torch.stack(rgb_inputs).cuda(), "pad_info": pads}
)
_, _, h, w = depths.shape
depths = depths[..., pad[0] : h - pad[1], pad[2] : w - pad[3]]
depths = depths * self.config.data_basic.depth_range[-1] / label_scale_factor
depths = torch.nn.functional.interpolate(depths, (H, W), mode="bilinear")
return depths.clamp(0, 300).squeeze(1).cpu().numpy()
@display_wrapper
def render_previews(
self,
frame: np.ndarray,
depth: np.ndarray,
intrinsics: list[float],
w2cs: np.ndarray,
):
"""
:param frame: `np.ndarray` of shape (H, W, C) and range (0, 255)
:param depth: `np.ndarray` of shape (H, W) and range (0, 300)
:param intrinsics: list of [fx, fy, cx, cy]
:param w2cs: `np.ndarray` of shape (4, 4)
:return: previews: `np.ndarray of shape (B, H, W, C) and range (0, 255)`
"""
H, W, _ = frame.shape
K = o3d.camera.PinholeCameraIntrinsic(W, H, *intrinsics)
pcd = project_point_cloud(frame, depth, intrinsics)
mat = o3d.visualization.rendering.MaterialRecord()
mat.shader = "defaultUnlit"
mat.point_size = 2
renderer = o3d.visualization.rendering.OffscreenRenderer(W, H)
renderer.scene.set_background(np.array([1.0, 1.0, 1.0, 1.0]))
renderer.scene.view.set_post_processing(False)
renderer.scene.clear_geometry()
renderer.scene.add_geometry("point cloud", pcd, mat)
previews = []
for w2c in tqdm(relative_pose(w2cs, mode="left")):
renderer.setup_camera(K, w2c)
previews.append(renderer.render_to_image())
return np.stack(previews)
@display_wrapper
def render_4d_scene(
self,
frames: np.ndarray,
depths: np.ndarray,
intrinsics: list[float],
w2cs: np.ndarray,
):
"""
:param frames: `np.ndarray` of shape (B, H, W, C) and range (0, 255)
:param depths: `np.ndarray` of shape (B, H, W) and range (0, 300)
:param intrinsics: list of [fx, fy, cx, cy]
:param w2cs: `np.ndarray` of shape (4, 4)
:return: renderings: `np.ndarray of shape (B, H, W, C) and range (0, 255)`
"""
F, H, W, _ = frames.shape
K = o3d.camera.PinholeCameraIntrinsic(W, H, *intrinsics)
renderer = o3d.visualization.rendering.OffscreenRenderer(W, H)
renderer.scene.set_background(np.array([1.0, 1.0, 1.0, 1.0]))
renderer.scene.view.set_post_processing(False)
c2w_0 = np.linalg.inv(w2cs[0])
eye_pos_world = (c2w_0 @ np.array([0.3, -0.5, -0.5, 1]))[:3]
center_pos_world = (c2w_0 @ np.array([0, 0, 2, 1]))[:3]
up_vector_world = np.array([0, -1, 0])
renderer.scene.camera.look_at(center_pos_world, eye_pos_world, up_vector_world)
point_material = o3d.visualization.rendering.MaterialRecord()
point_material.shader = "defaultUnlit"
point_material.point_size = 2
line_material = o3d.visualization.rendering.MaterialRecord()
line_material.shader = "unlitLine"
line_material.line_width = 3
renderings = []
for frame, depth, w2c in tqdm(zip(frames, depths, w2cs), total=F):
c2w = np.linalg.inv(w2c)
pcd = project_point_cloud(frame, depth, intrinsics)
pcd.transform(c2w)
wire_frame, frustum, frustum_material = create_camera_frustum(frame, K, c2w)
renderer.scene.clear_geometry()
renderer.scene.add_geometry("point cloud", pcd, point_material)
renderer.scene.add_geometry("wire frame", wire_frame, line_material)
renderer.scene.add_geometry("frustum", frustum, frustum_material)
renderings.append(renderer.render_to_image())
return np.stack(renderings)
if __name__ == "__main__":
with Display(visible=False, size=(512, 320)):
o3d.visualization.rendering.OffscreenRenderer(512, 320)
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