Batch Compress Videos

Why this matters

Library storage bills grow with every upload. Quality-targeted batch compression cuts size 30–70% while keeping visual quality within a defined score.

Per-file reports make the savings auditable — you can show the storage line going down.

How it works

Submit the folder with a CRF/VMAF target; each file is encoded independently and reported with before/after size and quality score.

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/encode/jobs"
headers = {"X-API-Key": "YOUR_API_KEY"}
payload = {"input": "s3://bucket/library/", "codec": "h264", "crf": 23, "pattern": "*.mov"}

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

• Run a 10-file pilot to size the expected savings before the full batch.
• Exclude already-efficient files (HEVC masters, short clips) via the pattern filter.
• Verify a sample per batch with the reported VMAF estimates.

Model the batch compress flow in Postman.