face-to-many 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    "face-to-many",
 9    seed=1321321,
10    image="https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg",
11    style="3D",
12    prompt="a person",
13    lora_scale=1,
14    prompt_strength=4.5,
15    denoising_strength=0.65,
16    instant_id_strength=1,
17    control_depth_strength=0.8,
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    "seed": 1321321,
29    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg",
30    "style": "3D",
31    "prompt": "a person",
32    "lora_scale": 1,
33    "prompt_strength": 4.5,
34    "denoising_strength": 0.65,
35    "instant_id_strength": 1,
36    "control_depth_strength": 0.8,
37}
38job = client.submit_async("face-to-many", **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)