viser4d 0.5.4

A viser extension with out-of-the-box support for the time dimension

viser4d

viser4d is a small wrapper around viser that adds a time dimension. It records scene operations across timesteps, supports timeline-synced audio playback, and can seek or play them back.

Quickstart

pip install viser4d

import numpy as np
import viser4d

server = viser4d.Viser4dServer(num_steps=10)

with server.at(0):
    points = np.random.uniform(-1.0, 1.0, size=(200, 3))
    point_cloud = server.scene.add_point_cloud(
        "/points",
        points=points,
        colors=(255, 200, 0),
    )

for i in range(1, 10):
    with server.at(i):
        points = np.random.uniform(-1.0, 1.0, size=(200, 3))
        point_cloud.points = points

server.play(fps=10, loop=True)
server.sleep_forever()

Streaming ingest

If data arrives incrementally, initialize components at t=0 and then record updates as each new frame arrives:

import numpy as np
import viser4d

num_steps = 180
server = viser4d.Viser4dServer(num_steps=num_steps)

def get_next_points() -> np.ndarray:
    # Replace with your real sensor/network/pipeline frame source.
    return np.random.normal(size=(400, 3)).astype(np.float32)

with server.at(0):
    point_cloud = server.scene.add_point_cloud(
        "/stream/points",
        points=get_next_points(),
    )

for t in range(1, num_steps):
    points = get_next_points()
    with server.at(t):
        point_cloud.points = points
    server.seek(t)  # optional: keep view synced to latest streamed frame

server.play(fps=30, loop=True)
server.sleep_forever()

Timestep callbacks

If you have your own visualization logic and just want to use viser4d's timeline infrastructure (playback controls, seeking, scrubbing), you can register a callback that fires whenever the timestep changes:

import viser4d

server = viser4d.Viser4dServer(num_steps=100)

def on_timestep(t: int) -> None:
    # Update your custom visualizations here
    update_video_frames(t)
    update_body_meshes(t)
    update_3d_keypoints(t)

server.on_timestep_change(on_timestep)
server.play(fps=30, loop=True)
server.sleep_forever()

Callbacks are invoked after viser4d applies its own recorded state, so you can mix both approaches - record some operations with at(t) and handle others via callbacks.

Serialize .viser recordings

To serialize across timesteps in memory, use server.serialize():

import viser4d

server = viser4d.Viser4dServer(num_steps=100)
# ... record timeline data ...
blob = server.serialize(start_timestep=0, end_timestep=None)

To write the recording to disk, use server.write_recording(...):

server.write_recording(
    "recording.viser",
    start_timestep=0,
    end_timestep=None,
)

Streaming audio append

For audio that arrives incrementally, create a track once inside at(t) and append chunks through the returned handle:

import numpy as np
import viser4d

server = viser4d.Viser4dServer(num_steps=300, fps=30)

with server.at(0):
    audio = server.scene.add_audio(
        "/stream/audio",
        data=np.zeros(1600, dtype=np.float32),
        sample_rate=16000,
    )

for _ in range(120):
    chunk = np.random.uniform(-0.05, 0.05, size=(1600,)).astype(np.float32)
    audio.append(chunk)

AudioHandle.append(...) extends the same track contiguously (same channel count).

How it works

Context determines behavior. server.scene is viser's normal scene API, but its websocket target is swapped while you're inside an at(t) context:

Inside at(t):                          Outside at(t):
─────────────                          ──────────────
scene.add_frame(...)                   scene.add_frame(...)
       │                                      │
       ▼                                      ▼
    records to Timeline                    forwards to live viser scene

• Inside at(t): Operations are recorded to a timeline, not executed.
• Outside at(t): Operations forward directly to viser's live scene.
• Playback: seek(t) or play() applies recorded state to the live scene.
• Audio: Add timeline-synced tracks with server.scene.add_audio(...).

See examples/ for more.

Quality checks

uvx ruff format .
uvx ruff check .
uvx ty check
pnpm run typecheck:runtime
pnpm run build:runtime

Tests

pnpm run build:runtime
uv run --group dev pytest -q