Tutorial · Python · ~10 min
Smooth Out Choppy Video Recordings
Screen recordings and phone footage stutter when frames drop. Interpolation fills the gaps.
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
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.
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