Smart Banner Resizer 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    "smart-banner-resizer",
 9    image_url="https://segmind-resources.s3.amazonaws.com/input/smart-banner-resizer-input.png",
10    target_sizes=["1080x1080", "1080x1920", "1200x628"],
11    num_images_per_size=1,
12    resolution="1K",
13    output_format="png",
14    safety_tolerance="4",
15)
16print(result["status"])                      # COMPLETED
17print(result.get("output"))                  # model output (e.g. media URL)
18print(result["metrics"]["inference_time"])   # server compute seconds
19
20# --- Or submit + poll manually (track request_id, control the cadence) ---
21from segmind import SegmindClient, InferenceFailed, InferenceTimeout
22
23client = SegmindClient()                      # reads SEGMIND_API_KEY
24payload = {
25    "image_url": "https://segmind-resources.s3.amazonaws.com/input/smart-banner-resizer-input.png",
26    "target_sizes": ["1080x1080", "1080x1920", "1200x628"],
27    "num_images_per_size": 1,
28    "resolution": "1K",
29    "output_format": "png",
30    "safety_tolerance": "4",
31}
32job = client.submit_async("smart-banner-resizer", **payload)
33print(job.request_id)                         # available immediately
34try:
35    result = job.wait(timeout=600, interval=1.0)
36except InferenceTimeout as e:
37    print("still running:", e.request_id)
38except InferenceFailed as e:
39    print("failed:", e.detail)