Stable Diffusion 3 Medium Image to Image 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    "sd3-med-img2img",
 9    prompt="photo of a boy holding phone on table,3d pixar style",
10    negative_prompt="low quality,less details",
11    image="https://segmind-sd-models.s3.amazonaws.com/display_images/sd3-img2img-ip.jpg",
12    num_inference_steps=20,
13    guidance_scale=5,
14    seed=698845,
15    samples=1,
16    strength=0.7,
17    sampler="dpmpp_2m",
18    scheduler="sgm_uniform",
19    base64=False,
20)
21print(result["status"])                      # COMPLETED
22print(result.get("output"))                  # model output (e.g. media URL)
23print(result["metrics"]["inference_time"])   # server compute seconds
24
25# --- Or submit + poll manually (track request_id, control the cadence) ---
26from segmind import SegmindClient, InferenceFailed, InferenceTimeout
27
28client = SegmindClient()                      # reads SEGMIND_API_KEY
29payload = {
30    "prompt": "photo of a boy holding phone on table,3d pixar style",
31    "negative_prompt": "low quality,less details",
32    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/sd3-img2img-ip.jpg",
33    "num_inference_steps": 20,
34    "guidance_scale": 5,
35    "seed": 698845,
36    "samples": 1,
37    "strength": 0.7,
38    "sampler": "dpmpp_2m",
39    "scheduler": "sgm_uniform",
40    "base64": False,
41}
42job = client.submit_async("sd3-med-img2img", **payload)
43print(job.request_id)                         # available immediately
44try:
45    result = job.wait(timeout=600, interval=1.0)
46except InferenceTimeout as e:
47    print("still running:", e.request_id)
48except InferenceFailed as e:
49    print("failed:", e.detail)