Face Detailer 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-detailer",
 9    image="https://segmind-sd-models.s3.amazonaws.com/display_images/face-detailer-test-ip.png",
10    prompt="clear face and natural skin",
11    negative_prompt="bad quality, painting, blur",
12    samples=1,
13    num_inference_steps=25,
14    guidance_scale=5,
15    seed=12467,
16    denoise=0.4,
17    image_format="jpeg",
18    image_quality=95,
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    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/face-detailer-test-ip.png",
31    "prompt": "clear face and natural skin",
32    "negative_prompt": "bad quality, painting, blur",
33    "samples": 1,
34    "num_inference_steps": 25,
35    "guidance_scale": 5,
36    "seed": 12467,
37    "denoise": 0.4,
38    "image_format": "jpeg",
39    "image_quality": 95,
40    "base64": False,
41}
42job = client.submit_async("face-detailer", **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)