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from __future__ import annotations
from dataclasses import asdict, dataclass
import hashlib
import json
import math
from pathlib import Path
import re
from functools import partial
import numpy as np
CHUNK_FRAMES = 33
FPS = 16
MAX_TRANSLATION = 5.0
DEFAULT_ORBIT_RADIUS = 2.0
ACTION_FIELDS = {
"forward": ("forward", 1),
"backward": ("forward", -1),
"left": ("right", -1),
"right": ("right", 1),
"up": ("up", 1),
"down": ("up", -1),
"yaw_left": ("yaw", -1),
"yaw_right": ("yaw", 1),
"pitch_up": ("pitch", 1),
"pitch_down": ("pitch", -1),
"orbit_left": ("orbit_yaw", -1),
"orbit_right": ("orbit_yaw", 1),
"orbit_up": ("orbit_pitch", 1),
"orbit_down": ("orbit_pitch", -1),
}
ALIASES = {
"f": "forward", "b": "backward", "l": "left", "r": "right",
"yl": "yaw_left", "yr": "yaw_right", "pu": "pitch_up", "pd": "pitch_down",
}
@dataclass(frozen=True)
class Action:
forward: float = 0.0
right: float = 0.0
yaw: float = 0.0
pitch: float = 0.0
speed: float = 1.0
up: float = 0.0
orbit: bool = False
orbit_radius: float = 0.0
def validate(self):
values = (self.forward, self.right, self.up, self.yaw, self.pitch)
if not all(math.isfinite(v) for v in (*values, self.speed)):
raise ValueError("Control values must be finite")
if sum(v != 0 for v in values) > 1:
raise ValueError("Only one movement or rotation may be active per chunk")
if not math.isfinite(self.orbit_radius) or self.orbit_radius < 0:
raise ValueError("Orbit radius must be finite and non-negative")
def normalized(self):
"""Apply the interactive controls' slider limits."""
self.validate()
return Action(
forward=max(-1.0, min(1.0, self.forward)),
right=max(-1.0, min(1.0, self.right)),
up=max(-1.0, min(1.0, self.up)),
yaw=max(-45.0, min(45.0, self.yaw)),
pitch=max(-45.0, min(45.0, self.pitch)),
speed=max(0.1, min(MAX_TRANSLATION, self.speed)),
orbit=self.orbit,
orbit_radius=self.orbit_radius,
)
def json(self):
return asdict(self)
def parse_event(event: str) -> tuple[str, float]:
match = re.fullmatch(r"([a-z_]+)([0-9]+(?:\.[0-9]+)?)", event.lower())
if match is None:
raise ValueError(f"Invalid action {event!r}; use e.g. forward1 or yaw_left30")
name, value = match.groups()
name = ALIASES.get(name, name)
if name not in ACTION_FIELDS:
raise ValueError(f"Unknown action {name!r}; choose from {', '.join(ACTION_FIELDS)}")
amount = float(value)
if not math.isfinite(amount):
raise ValueError(f"Action amount must be finite: {event}")
if ACTION_FIELDS[name][0] in {"forward", "right", "up"} and amount > MAX_TRANSLATION:
raise ValueError(f"{event}: translation must not exceed {MAX_TRANSLATION:g} per chunk")
return name, amount
def parse_actions(text: str) -> list[str]:
"""Expand space/comma-separated actions, xN repetitions, and # comments."""
text = re.sub(r"#[^\n]*", "", text)
text = re.sub(r"\s*&\s*", "&", text)
events = []
for token in re.split(r"[\s,]+", text.strip()):
if not token:
continue
match = re.fullmatch(r"(.+?)(?:x([1-9][0-9]*))?", token.lower())
event, repeat = match.groups()
if re.fullmatch(r"reverse(?:_frames)?[1-9][0-9]*", event):
canonical = event
else:
parts = []
axes = set()
for component in event.split("&"):
name, _ = parse_event(component)
field = ACTION_FIELDS[name][0]
if field in axes:
raise ValueError(f"An action may use each axis only once: {event}")
axes.add(field)
value = re.search(r"[0-9].*", component).group()
parts.append(name + value)
canonical = "&".join(parts)
events.extend([canonical] * int(repeat or 1))
if not events:
raise ValueError("Provide at least one camera action")
return events
def parse_trajectory(text: str) -> tuple[list[str], dict[str, str | float]]:
"""Read actions and trajectory settings from text."""
choices = {
"dtype": {"float32", "float64"},
"sampling": {"linear", "smooth_turns"},
"last_frame": {"exclude", "include"},
}
options, lines = {}, []
for line in text.splitlines():
line = line.split("#", 1)[0].strip()
if line.startswith("@"):
fields = line[1:].split()
if len(fields) == 2 and fields[0] == "orbit_radius" and not lines:
radius = float(fields[1])
if not math.isfinite(radius) or radius < 0:
raise ValueError("Orbit radius must be finite and non-negative")
options["orbit_radius"] = radius
continue
if len(fields) != 2 or fields[0] not in choices or fields[1] not in choices[fields[0]]:
raise ValueError(f"Invalid trajectory setting: {line}")
if lines:
raise ValueError("Trajectory settings must precede the actions")
options[fields[0]] = fields[1]
elif line:
lines.append(line)
return parse_actions("\n".join(lines)), options
def count_chunks(events: list[str]) -> int:
return sum(
int(re.search(r"[0-9]+$", event).group()) if event.startswith("reverse") else 1
for event in events
)
def action_from_event(event: str, orbit_radius: float = DEFAULT_ORBIT_RADIUS) -> Action:
name, amount = parse_event(event)
field, sign = ACTION_FIELDS[name]
if field.startswith("orbit_"):
return Action(**{field[6:]: sign * amount}, orbit=True, orbit_radius=orbit_radius)
if field in {"yaw", "pitch"}:
return Action(**{field: sign * amount})
return Action(**{field: sign}, speed=amount)
def rotation_y(degrees: float) -> np.ndarray:
angle = math.radians(degrees)
cosine, sine = math.cos(angle), math.sin(angle)
return np.asarray(
((cosine, 0.0, sine), (0.0, 1.0, 0.0), (-sine, 0.0, cosine)),
dtype=np.float64,
)
def relative_poses(chunk: np.ndarray) -> np.ndarray:
"""Convert a global c2w chunk to FP32 poses relative to its first frame."""
homogeneous = np.zeros((len(chunk), 4, 4), dtype=np.float64)
homogeneous[:, :3, :4] = np.asarray(chunk)[:, :3, :4]
homogeneous[:, 3, 3] = 1.0
relative = np.linalg.inv(homogeneous[0])[None] @ homogeneous
return relative[:, :3, :4].astype(np.float32)
def rotation_x(degrees: float) -> np.ndarray:
angle = math.radians(degrees)
cosine, sine = math.cos(angle), math.sin(angle)
return np.asarray(
((1.0, 0.0, 0.0), (0.0, cosine, -sine), (0.0, sine, cosine)),
dtype=np.float64,
)
def horizontal_direction(rotation: np.ndarray, forward: bool) -> np.ndarray:
axis = rotation[:, 2 if forward else 0].copy()
axis[1] = 0.0
norm = np.linalg.norm(axis)
if norm < 1e-8:
# Keep a horizontal heading when looking straight up or down.
other = rotation[:, 0 if forward else 2]
axis = np.array([-other[2], 0.0, other[0]])
if not forward:
axis = -axis
norm = np.linalg.norm(axis)
return axis / norm
def sample_chunk(
start: np.ndarray, action: Action, *, fractions: np.ndarray | None = None,
) -> tuple[np.ndarray, np.ndarray]:
"""Sample one action; the logical endpoint starts the next chunk."""
action.validate()
alpha = np.arange(CHUNK_FRAMES, dtype=np.float64) / CHUNK_FRAMES if fractions is None else fractions
poses = np.repeat(start[None], len(alpha), axis=0)
end = start.copy()
if action.yaw or action.pitch:
def rotated(fraction):
if action.yaw:
return rotation_y(action.yaw * fraction) @ start[:3, :3]
return start[:3, :3] @ rotation_x(action.pitch * fraction)
for index, fraction in enumerate(alpha):
poses[index, :3, :3] = rotated(fraction)
end[:3, :3] = rotated(1.0)
if action.orbit and action.orbit_radius:
radius = action.orbit_radius
angle = math.radians(abs(action.yaw or action.pitch))
if radius * angle > MAX_TRANSLATION + 1e-12:
raise ValueError("Orbit arc length must not exceed 5 per chunk; reduce radius or angle")
center = start[:3, 3] + radius * start[:3, 2]
poses[:, :3, 3] = center - radius * poses[:, :3, 2]
if alpha[0] == 0:
poses[0, :3, 3] = start[:3, 3]
end[:3, 3] = center - radius * end[:3, 2]
else:
if action.up:
direction = np.array([0.0, -action.up, 0.0])
elif action.forward:
direction = action.forward * horizontal_direction(start[:3, :3], True)
else:
direction = action.right * horizontal_direction(start[:3, :3], False)
delta = action.speed * direction
if np.linalg.norm(delta) > MAX_TRANSLATION + 1e-12:
raise ValueError(f"Translation must not exceed {MAX_TRANSLATION:g} per chunk")
poses[:, :3, 3] = start[:3, 3] + alpha[:, None] * delta
end[:3, 3] = start[:3, 3] + delta
return poses, end
def _sample_event(start: np.ndarray, event: str, fractions: np.ndarray, orbit_radius=DEFAULT_ORBIT_RADIUS) -> np.ndarray:
components = event.split("&")
if len(components) == 1:
return sample_chunk(start, action_from_event(event, orbit_radius), fractions=fractions)[0]
if any(part.startswith("orbit_") for part in components):
raise ValueError("Use orbit as a separate action")
poses = np.repeat(start[None], len(fractions), axis=0)
delta = np.zeros(3)
for component in components:
action = action_from_event(component)
if action.yaw:
for index, fraction in enumerate(fractions):
poses[index, :3, :3] = rotation_y(action.yaw * fraction) @ poses[index, :3, :3]
elif action.pitch:
for index, fraction in enumerate(fractions):
poses[index, :3, :3] = poses[index, :3, :3] @ rotation_x(action.pitch * fraction)
else:
_, end = sample_chunk(start, action)
delta += end[:3, 3] - start[:3, 3]
if np.linalg.norm(delta) > MAX_TRANSLATION + 1e-12:
raise ValueError(f"{event}: combined translation must not exceed {MAX_TRANSLATION:g} per chunk")
poses[:, :3, 3] = start[:3, 3] + fractions[:, None] * delta
return poses
def _sample_curve(start, event, tangent_start, tangent_end, times, *, orbit_radius=DEFAULT_ORBIT_RADIUS):
fractions = times
if tangent_start is not None:
fractions = (
-2 * times**3 + 3 * times**2
+ (times**3 - 2 * times**2 + times) * tangent_start
+ (times**3 - times**2) * tangent_end
)
return _sample_event(start, event, fractions, orbit_radius)
def _reverse_curve(curve, times):
return curve(1.0 - times)
def _reverse_sampled_curve(curve, last_time, times):
return curve(last_time * (1.0 - times))
def build_trajectory(
events: list[str], *, dtype: str = "float64", sampling: str = "linear",
last_frame: str = "exclude", orbit_radius: float = DEFAULT_ORBIT_RADIUS,
) -> tuple[np.ndarray, list[dict[str, object]]]:
if not events:
raise ValueError("Provide at least one camera action")
if not math.isfinite(orbit_radius) or orbit_radius < 0:
raise ValueError("Orbit radius must be finite and non-negative")
world = np.eye(4, dtype=np.float64)
chunks, records, curves, sample_times = [], [], [], []
def append(event, curve, times, poses=None):
nonlocal world
start, end = curve(np.array([0.0, 1.0]))
chunks.append(curve(times) if poses is None else poses)
records.append({
"chunk_index": len(records), "event": event,
"logical_start_c2w": start.tolist(), "logical_end_c2w": end.tolist(),
})
curves.append(curve)
sample_times.append(times)
world = end
for index, event in enumerate(events):
if event.startswith("reverse"):
count = int(re.search(r"[0-9]+$", event).group())
if count > len(chunks):
raise ValueError(f"{event} needs {count} preceding chunks; only {len(chunks)} exist")
indices = list(range(len(chunks) - 1, len(chunks) - count - 1, -1))
for source in indices:
if event.startswith("reverse_frames"):
curve = partial(_reverse_sampled_curve, curves[source], sample_times[source][-1])
times = np.linspace(0.0, 1.0, CHUNK_FRAMES)
append(event, curve, times, chunks[source][::-1].copy())
else:
curve = partial(_reverse_curve, curves[source])
include_end = last_frame == "include" and index == len(events) - 1 and source == indices[-1]
times = (
np.linspace(0.0, 1.0, CHUNK_FRAMES) if include_end
else np.arange(CHUNK_FRAMES, dtype=np.float64) / CHUNK_FRAMES
)
poses = None
original = records[source]["event"]
if sampling == "linear" and "&" not in original and not original.startswith("reverse"):
action = action_from_event(original)
if not action.yaw and not action.pitch and sample_times[source][-1] < 1.0 and not include_end:
# Reuse linear translation samples without another interpolation roundoff.
endpoint = np.array(records[source]["logical_end_c2w"])
poses = np.concatenate([endpoint[None], chunks[source][1:][::-1]])
append(event, curve, times, poses)
continue
smooth = sampling == "smooth_turns"
entering = index > 0 and events[index - 1] == event
leaving = index + 1 < len(events) and events[index + 1] == event
include_end = (smooth and not leaving) or (last_frame == "include" and index == len(events) - 1)
times = (
np.linspace(0.0, 1.0, CHUNK_FRAMES) if include_end
else np.arange(CHUNK_FRAMES, dtype=np.float64) / CHUNK_FRAMES
)
curve = partial(
_sample_curve, world.copy(), event,
float(entering) if smooth else None, float(leaving),
orbit_radius=orbit_radius,
)
append(event, curve, times)
return np.concatenate(chunks).astype(dtype), records
def save_trajectory(
directory: Path, camera: np.ndarray, records: list[dict[str, object]], *, fps: int = FPS,
events: list[str] | None = None, options: dict[str, str | float] | None = None,
) -> Path:
directory.mkdir(parents=True, exist_ok=True)
camera_path = directory / "camera.npy"
np.save(camera_path, camera[:, :3, :4])
events = events if events is not None else [record["event"] for record in records]
headers = [f"@{key} {value}" for key, value in (options or {}).items()]
(directory / "actions.txt").write_text("\n".join(headers + events) + "\n", encoding="utf-8")
manifest = {
"format": "worldcrafter_camera_trajectory_v1",
"fps": fps,
"chunk_frames": CHUNK_FRAMES,
"num_chunks": len(records),
"num_frames": len(camera),
"motion_sequence": events,
"options": options or {},
"camera": camera_path.name,
"camera_semantics": "global metric c2w; x right, y down, z forward",
"sha256": {"camera": hashlib.sha256(camera_path.read_bytes()).hexdigest()},
"chunks": records,
}
(directory / "trajectory.json").write_text(
json.dumps(manifest, indent=2) + "\n", encoding="utf-8",
)
return camera_path
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