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on
Zero
Running
on
Zero
File size: 3,966 Bytes
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import numpy as np
import pycolmap
def _create_camera_params(frame_idx, cam_matrices, model_type, distortion_coeffs=None):
"""Build camera parameter array for different model types."""
if model_type == "PINHOLE":
return np.array([
cam_matrices[frame_idx][0, 0], cam_matrices[frame_idx][1, 1],
cam_matrices[frame_idx][0, 2], cam_matrices[frame_idx][1, 2]
])
elif model_type == "SIMPLE_PINHOLE":
focal_avg = (cam_matrices[frame_idx][0, 0] + cam_matrices[frame_idx][1, 1]) / 2
return np.array([focal_avg, cam_matrices[frame_idx][0, 2], cam_matrices[frame_idx][1, 2]])
elif model_type == "SIMPLE_RADIAL":
raise NotImplementedError("SIMPLE_RADIAL model not supported")
else:
raise ValueError(f"Unsupported camera model: {model_type}")
def _setup_camera_object(frame_idx, cam_matrices, img_dims, model_type, use_shared):
"""Create and configure camera object."""
if use_shared and frame_idx > 0:
return None
params = _create_camera_params(frame_idx, cam_matrices, model_type)
return pycolmap.Camera(
model=model_type,
width=img_dims[0],
height=img_dims[1],
params=params,
camera_id=frame_idx + 1
)
def _process_frame_points(scene_points, point_coords, frame_idx):
"""Extract and process 2D points belonging to specific frame."""
frame_mask = point_coords[:, 2].astype(np.int32) == frame_idx
valid_indices = np.nonzero(frame_mask)[0]
point2d_list = []
for idx, batch_idx in enumerate(valid_indices):
point3d_id = batch_idx + 1
xy_coords = point_coords[batch_idx][:2]
point2d_list.append(pycolmap.Point2D(xy_coords, point3d_id))
# Update track information
track = scene_points.points3D[point3d_id].track
track.add_element(frame_idx + 1, idx)
return point2d_list
def build_pycolmap_reconstruction(
points,
pixel_coords,
point_colors,
poses,
intrinsics,
image_size,
shared_camera_model=False,
camera_model="SIMPLE_PINHOLE",
):
"""
Convert numpy arrays to pycolmap reconstruction format.
Creates 3D scene structure without track optimization.
Suitable for initialization of neural rendering methods.
"""
num_frames = len(poses)
num_points = len(points)
scene = pycolmap.Reconstruction()
# Add 3D points to scene
for pt_idx in range(num_points):
scene.add_point3D(points[pt_idx], pycolmap.Track(), point_colors[pt_idx])
current_camera = None
# Process each frame
for frame_idx in range(num_frames):
# Setup camera if needed
if current_camera is None or not shared_camera_model:
current_camera = _setup_camera_object(
frame_idx, intrinsics, image_size, camera_model, shared_camera_model
)
scene.add_camera(current_camera)
# Create pose transformation
rotation_matrix = poses[frame_idx][:3, :3]
translation_vec = poses[frame_idx][:3, 3]
world_to_cam = pycolmap.Rigid3d(pycolmap.Rotation3d(rotation_matrix), translation_vec)
# Create image object
frame_image = pycolmap.Image(
id=frame_idx + 1,
name=f"frame_{frame_idx + 1}",
camera_id=current_camera.camera_id,
cam_from_world=world_to_cam
)
# Process 2D points for this frame
frame_points = _process_frame_points(scene, pixel_coords, frame_idx)
# Set image points and registration status
try:
frame_image.points2D = pycolmap.ListPoint2D(frame_points)
frame_image.registered = True
except:
print(f"Warning: Frame {frame_idx + 1} has no valid points")
frame_image.registered = False
scene.add_image(frame_image)
return scene |