Nomos Image Upscaler 4k Serverless API

 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3import segmind
 4
 5# Async (v2): submit to the queue and block until COMPLETED.
 6# run() returns the final result dict (600s deadline, 1.0s poll by default).
 7result = segmind.run(
 8    "nomos-upscaler",
 9    image="https://segmind-resources.s3.amazonaws.com/input/557ae4e3-8057-4668-bf41-ff836d0f73b0-test_upscale_1234142.jpg",
10    image_format="png",
11    image_quality=95,
12    base64=False,
13)
14print(result["status"])                      # COMPLETED
15print(result.get("output"))                  # model output (e.g. media URL)
16print(result["metrics"]["inference_time"])   # server compute seconds
17
18# --- Or submit + poll manually (track request_id, control the cadence) ---
19from segmind import SegmindClient, InferenceFailed, InferenceTimeout
20
21client = SegmindClient()                      # reads SEGMIND_API_KEY
22payload = {
23    "image": "https://segmind-resources.s3.amazonaws.com/input/557ae4e3-8057-4668-bf41-ff836d0f73b0-test_upscale_1234142.jpg",
24    "image_format": "png",
25    "image_quality": 95,
26    "base64": False,
27}
28job = client.submit_async("nomos-upscaler", **payload)
29print(job.request_id)                         # available immediately
30try:
31    result = job.wait(timeout=600, interval=1.0)
32except InferenceTimeout as e:
33    print("still running:", e.request_id)
34except InferenceFailed as e:
35    print("failed:", e.detail)