Tutorial · Python · ~10 min

Smooth Out Choppy Video Recordings

Screen recordings and phone footage stutter when frames drop. Interpolation fills the gaps.

PythonChoppy FootageAPI

Why this matters

Dropped frames make motion stutter — the video is missing its middle. Interpolation reconstructs the missing frames so motion flows.

This is the same engine as slow-mo, applied to a different problem: restoring cadence instead of creating time.

How it works

Submit with a small factor (1.5–2) and motion=smooth; the API rebuilds a steady frame cadence.

Submit a job with an input URL (S3, GCS or HTTPS), poll the job URL, and download the rendered output. No GPU, no queues, no ffmpeg builds to babysit.

Code

Python
import requests, time

API = "https://api.mlslabs.io/v1/frame-interpolation/jobs"
headers = {"X-API-Key": "YOUR_API_KEY"}
payload = {"input": "s3://bucket/clip.mp4", "factor": 1.5, "motion": "smooth"}

resp = requests.post(API, json=payload, headers=headers)
job = resp.json()
while job["status"] not in ("succeeded", "failed"):
    time.sleep(3)
    job = requests.get(job["url"], headers=headers).json()

print("Output:", job["output_url"])

Pro tips

  • Factor 1.5–2 is usually enough; more risks artifacts.
  • Stabilize first if the stutter comes with camera shake.
  • Keep the original — the smoothed version is a new deliverable.

Pricing note

Usage is metered per minute of media processed; the first tier is free each month. Volume discounts kick in automatically.

FAQ

Common questions

Can it fix variable frame rate (VFR) recordings?

VFR sources are normalized to CFR first, then interpolated — the API handles both in one job.

Will it fix audio sync?

No — audio is passed through; sync issues need an audio editor.

Is it good for lecture recordings?

Yes — talking-head footage smooths cleanly with minimal compute.