burns

Ken Burns pan/zoom video effects: turn a still image — or a sequence of stills — into a cinematic pan/zoom film.

The Ken Burns effect animates a static photograph by slowly panning across it and zooming in or out, giving still images a sense of motion. burns does exactly that, with a tiny API and no configuration required — and a clean, render-agnostic motion spec underneath so the same path drives the Python renderer here and the TypeScript one in ts/.

pip install burns

burns needs ffmpeg available on your system (moviepy uses it to encode video). On macOS: brew install ffmpeg. On Debian/Ubuntu: sudo apt-get install ffmpeg.

Demo

Starting from a single still image:

…two lines of code turn it into two different Ken Burns films — a slow zoom-in ("push") and a lateral pan ("drift"):

from burns import ken_burns_video, ken_burns_path

ken_burns_video(
    "demo_landscape.jpg", ken_burns_path(1, zoom=1.4, pan=0.06), duration=4.0
)
ken_burns_video(
    "demo_landscape.jpg", ken_burns_path(2, style="drift", pan=0.14), duration=4.0
)

style="push" — eased zoom-in	style="drift" — lateral pan

The full script that generated this still and these GIFs is misc/generate_demo.py.

Quickstart

A standard 2-second push-in, written next to the source image:

from burns import ken_burns_video

ken_burns_video("photo.jpg")  # → photo_kenburns.mp4

That's it. The result is an mp4 that slowly zooms into the center of photo.jpg.

The motion spec: BurnsPath

The camera motion is a BurnsPath — a pure, time-parameterized spec. Its core is evaluate(t) -> Rect for t ∈ [0, 1]: where the viewport is at each instant, independent of any renderer, frame rate, or duration.

A rect is Rect(x, y, w, h) — a normalized window over the image, top-left origin, every component in [0, 1]. Rect(0, 0, 1, 1) is the whole image; a smaller w/h is zoomed in. The common cases have one-liners:

from burns import ken_burns_video, BurnsPath, Rect

# The 90% case: push from the full image toward a point at a given zoom.
ken_burns_video("photo.jpg", BurnsPath.push_in(1.3, to=(0.65, 0.40)), duration=5.0)

# The canonical two-rectangle (Start → End) case, full control:
path = BurnsPath.from_start_end(
    Rect(0, 0, 1, 1),  # start: whole image
    Rect.from_center_zoom(0.65, 0.40, 1.2),  # end: zoomed toward upper-right
    easing="ease-in-out",  # the cinematic default
)
ken_burns_video("photo.jpg", path, duration=5.0, saveas="out.mp4")

# N keyframes for a multi-beat move (a hold = two equal keyframes):
path = BurnsPath(
    keyframes=[
        (0.0, Rect(0, 0, 1, 1)),
        (0.5, Rect.from_center_zoom(0.65, 0.40, 1.2)),
        (1.0, Rect.from_center_zoom(0.35, 0.60, 1.3)),
    ]
)

Easing is a CSS timing function ("linear", "ease-in-out" (default), "cubic-bezier(...)", or any callable) and is composed over the geometry — motion shape and motion speed stay orthogonal.

Output aspect ratio is independent of the source image. Set output_aspect to make a widescreen clip from a portrait photo (the renderer cover-crops, never stretches):

ken_burns_video(
    "portrait.jpg", BurnsPath.push_in(1.4, output_aspect=16 / 9), duration=6.0
)

Let burns design the motion for you

Hand-authoring rectangles for every image gets tedious. ken_burns_path generates a cohesive, deterministic, non-repetitive path from a little intent — pass the image's position (index) and it picks the framing. Duration is supplied at render time, so a path is reusable across clip lengths:

from burns import ken_burns_video, ken_burns_path

# index seeds the focal direction; odd indices push in, even pull out.
ken_burns_video("photo.jpg", ken_burns_path(1), duration=5.0)

# styles: "push" (zoom-led, the default) or "drift" (pure horizontal pan)
ken_burns_video("photo.jpg", ken_burns_path(2, style="drift"), duration=5.0)

# easing controls the velocity curve (default "ease-in-out"); "linear" is constant
ken_burns_video("photo.jpg", ken_burns_path(1, easing="linear"), duration=6.0)

Content-aware motion

ken_burns_path frames by index, not by what is in the picture — so it will happily drift across empty sky. content_aware_path_for looks at the image first and builds a path that keeps the subject framed:

from burns import ken_burns_video, content_aware_path_for

ken_burns_video("photo.jpg", content_aware_path_for("photo.jpg", index=1), duration=5.0)

No extra install: the subject estimate is a gradient-magnitude ("busyness") heuristic over numpy + Pillow, which burns already requires. Flat regions — sky, walls, water — have low gradient and fall away, so the box tracks the detailed part of the frame.

Faces, when you have a detector. burns ships no face model. Detection is injected, so you choose the dependency: pass boxes you already have, or a faces_detector callable that returns normalized (x, y, w, h) boxes. The detector always receives a PIL.Image — whatever you passed as image is opened or converted first.

# boxes you already have (faces win over the saliency estimate)
path = content_aware_path_for("group.jpg", faces=[(0.31, 0.22, 0.09, 0.12)])

# or a detector — anything callable: OpenCV, ONNX, a vision model, a lookup
path = content_aware_path_for("group.jpg", faces_detector=my_detector, index=2)

With neither faces nor faces_detector you simply get saliency-only, sky-avoiding motion — no error, no warning, just a less specific keep-region.

The geometry on its own. content_aware_path is the pixel-free core: give it the image size and a keep-region and it returns the BurnsPath. Reach for it when the boxes come from somewhere else — a UI, a database, an upstream vision pipeline.

from burns import content_aware_path

path = content_aware_path(
    1920, 1080, subject=(0.60, 0.55, 0.20, 0.25), index=1, output_aspect=16 / 9
)

Start and end windows are both centered on the keep-region (sliding inside the image edges when they'd overhang) and sized to the output aspect, so the renderer's cover-crop is a no-op — what you frame is what shows.

The requested zoom is capped so the padded keep-region normally stays inside the frame — but a min_zoom + 0.02 floor wins over that cap, so a keep-region that fills the picture is cropped slightly rather than yielding no motion at all. If a subject that fills the frame must stay whole, tighten the keep-region (a smaller keep_pad, or explicit boxes); raising zoom cannot do it. index keeps the same rhythm as ken_burns_path (odd pushes in, even pulls out); mode="in" / mode="out" overrides it.

Multi-image films

ken_burns_film renders a sequence of (image, path, duration_s) panels as one continuous film — a single encode pass, so there are no concatenation seams and no per-image freeze frames at the cuts. Pass an optional pre-built audio track to mux it in.

from burns import ken_burns_film, ken_burns_path

panels = [
    ("a.jpg", ken_burns_path(1), 4.0),
    ("b.jpg", ken_burns_path(2), 4.0),
    ("c.jpg", ken_burns_path(3), 4.0),
]
ken_burns_film(panels, saveas="film.mp4", fps=30, audio_path="narration.mp3")

Interop: one spec, many renderers

A BurnsPath serializes to a small versioned JSON document via path.to_dict() (and back via BurnsPath.from_dict(...)). That is the wire format, and it is already shared across two languages: kenburnz is a TypeScript port of the same evaluate(t) math, living in this repo's ts/ directory and published to npm. It is pinned to the Python side by a shared golden-vector fixture, and adds browser-only pieces: a zero-cost CSS transform preview, a WebCodecs .webm exporter, and mountPathEntry — a headless component for authoring a path in a UI. It is young (0.0.1), and its browser-only paths are verified locally rather than in CI. No renderer owns the motion.

API