SD Outpainting 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    "sd1.5-outpaint",
 9    image="https://segmind.com/image5.png",
10    prompt="streets in italy",
11    negative_prompt="NONE",
12    scheduler="DDIM",
13    num_inference_steps=25,
14    img_width=1024,
15    img_height=1024,
16    scale=1,
17    strength=1,
18    offset_x=256,
19    offset_y=256,
20    guidance_scale=7.5,
21    mask_expand=8,
22    seed=124567,
23)
24print(result["status"])                      # COMPLETED
25print(result.get("output"))                  # model output (e.g. media URL)
26print(result["metrics"]["inference_time"])   # server compute seconds
27
28# --- Or submit + poll manually (track request_id, control the cadence) ---
29from segmind import SegmindClient, InferenceFailed, InferenceTimeout
30
31client = SegmindClient()                      # reads SEGMIND_API_KEY
32payload = {
33    "image": "https://segmind.com/image5.png",
34    "prompt": "streets in italy",
35    "negative_prompt": "NONE",
36    "scheduler": "DDIM",
37    "num_inference_steps": 25,
38    "img_width": 1024,
39    "img_height": 1024,
40    "scale": 1,
41    "strength": 1,
42    "offset_x": 256,
43    "offset_y": 256,
44    "guidance_scale": 7.5,
45    "mask_expand": 8,
46    "seed": 124567,
47}
48job = client.submit_async("sd1.5-outpaint", **payload)
49print(job.request_id)                         # available immediately
50try:
51    result = job.wait(timeout=600, interval=1.0)
52except InferenceTimeout as e:
53    print("still running:", e.request_id)
54except InferenceFailed as e:
55    print("failed:", e.detail)