Topaz Labs Video Upscale Serverless API

 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
 4
 5# Async (v2) — recommended for long-running / video models.
 6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
 7# deadline and keeps the request_id so you can re-poll later.
 8client = SegmindClient()                      # reads SEGMIND_API_KEY
 9payload = {
10    "video": "https://segmind-resources.s3.amazonaws.com/input/008b1c8e-5d9c-4ad3-96e3-0943f120058f-273289_medium.mp4",
11    "target_fps": 60,
12    "target_resolution": "1080p",
13}
14job = client.submit_async("topaz-video-upscale", **payload)
15print(job.request_id)                         # available immediately
16try:
17    result = job.wait(timeout=900, interval=2.0)
18    print(result["status"])                  # COMPLETED
19    print(result.get("output"))              # model output (e.g. video URL)
20except InferenceTimeout as e:
21    print("still running:", e.request_id)    # re-poll later with this id
22except InferenceFailed as e:
23    print("failed:", e.detail)
24
25# Fast models (<=600s) can use the one-liner instead:
26# result = segmind.run("topaz-video-upscale", **payload)