material-transfer 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    "material-transfer",
 9    steps=6,
10    prompt="marble sculpture",
11    max_width=1920,
12    max_height=1920,
13    output_format="webp",
14    subject_image="https://segmind-sd-models.s3.amazonaws.com/display_images/bird.png",
15    guidance_scale=2,
16    material_image="https://segmind-sd-models.s3.amazonaws.com/display_images/ruby.png",
17    output_quality=80,
18    material_strength="medium",
19    return_intermediate_images=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    "steps": 6,
31    "prompt": "marble sculpture",
32    "max_width": 1920,
33    "max_height": 1920,
34    "output_format": "webp",
35    "subject_image": "https://segmind-sd-models.s3.amazonaws.com/display_images/bird.png",
36    "guidance_scale": 2,
37    "material_image": "https://segmind-sd-models.s3.amazonaws.com/display_images/ruby.png",
38    "output_quality": 80,
39    "material_strength": "medium",
40    "return_intermediate_images": False,
41}
42job = client.submit_async("material-transfer", **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)