Segmind SegFit v1.2 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    "segfit-v1.2",
 9    outfit_image="https://segmind-resources.s3.amazonaws.com/others/c63e9544-10da-45cd-81f9-725fb98ca0c0-090a11c5-4e9a-42f2-8cf7-d74de7e1ebcf.png",
10    model_image="https://segmind-resources.s3.amazonaws.com/others/be81a5a2-a928-47d2-927e-cdc4cf25cb96-model_1.png",
11    model_type="Balanced",
12    cn_strength=0.35,
13    cn_end=0.35,
14    image_format="png",
15    image_quality=90,
16    seed=42,
17    base64=False,
18)
19print(result["status"])                      # COMPLETED
20print(result.get("output"))                  # model output (e.g. media URL)
21print(result["metrics"]["inference_time"])   # server compute seconds
22
23# --- Or submit + poll manually (track request_id, control the cadence) ---
24from segmind import SegmindClient, InferenceFailed, InferenceTimeout
25
26client = SegmindClient()                      # reads SEGMIND_API_KEY
27payload = {
28    "outfit_image": "https://segmind-resources.s3.amazonaws.com/others/c63e9544-10da-45cd-81f9-725fb98ca0c0-090a11c5-4e9a-42f2-8cf7-d74de7e1ebcf.png",
29    "model_image": "https://segmind-resources.s3.amazonaws.com/others/be81a5a2-a928-47d2-927e-cdc4cf25cb96-model_1.png",
30    "model_type": "Balanced",
31    "cn_strength": 0.35,
32    "cn_end": 0.35,
33    "image_format": "png",
34    "image_quality": 90,
35    "seed": 42,
36    "base64": False,
37}
38job = client.submit_async("segfit-v1.2", **payload)
39print(job.request_id)                         # available immediately
40try:
41    result = job.wait(timeout=600, interval=1.0)
42except InferenceTimeout as e:
43    print("still running:", e.request_id)
44except InferenceFailed as e:
45    print("failed:", e.detail)