Segmind SegFit v1.1 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-v1.1",
 9    outfit_image="https://segmind-inference-inputs.s3.ap-south-1.amazonaws.com/a8b0d0b4-8b45-4ff4-b42e-66c96c0070ee.jpeg",
10    background_description="aesthetic studio shoot",
11    aspect_ratio="2:3",
12    model_type="Balanced",
13    controlnet_type="Depth",
14    cn_strength=0.3,
15    cn_end=0.3,
16    image_format="png",
17    image_quality=95,
18    seed=-1,
19    upscale=False,
20    base64=False,
21)
22print(result["status"])                      # COMPLETED
23print(result.get("output"))                  # model output (e.g. media URL)
24print(result["metrics"]["inference_time"])   # server compute seconds
25
26# --- Or submit + poll manually (track request_id, control the cadence) ---
27from segmind import SegmindClient, InferenceFailed, InferenceTimeout
28
29client = SegmindClient()                      # reads SEGMIND_API_KEY
30payload = {
31    "outfit_image": "https://segmind-inference-inputs.s3.ap-south-1.amazonaws.com/a8b0d0b4-8b45-4ff4-b42e-66c96c0070ee.jpeg",
32    "background_description": "aesthetic studio shoot",
33    "aspect_ratio": "2:3",
34    "model_type": "Balanced",
35    "controlnet_type": "Depth",
36    "cn_strength": 0.3,
37    "cn_end": 0.3,
38    "image_format": "png",
39    "image_quality": 95,
40    "seed": -1,
41    "upscale": False,
42    "base64": False,
43}
44job = client.submit_async("segfit-v1.1", **payload)
45print(job.request_id)                         # available immediately
46try:
47    result = job.wait(timeout=600, interval=1.0)
48except InferenceTimeout as e:
49    print("still running:", e.request_id)
50except InferenceFailed as e:
51    print("failed:", e.detail)