Supir Photo-Realistic Image Restoration 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    "supir",
 9    image="https://segmind-resources.s3.amazonaws.com/input/557ae4e3-8057-4668-bf41-ff836d0f73b0-test_upscale_1234142.jpg",
10    s_cfg=7.5,
11    s_churn=5,
12    s_noise=1.003,
13    upscale=1,
14    a_prompt="Cinematic, High Contrast, ultra HD, hyper detailed.",
15    min_size=1024,
16    n_prompt="worst quality, low quality, frames, watermark.",
17    s_stage1=-1,
18    s_stage2=1,
19    edm_steps=50,
20    use_llava=True,
21    linear_CFG=False,
22    model_name="SUPIR-v0Q",
23    color_fix_type="Wavelet",
24    spt_linear_CFG=1,
25    linear_s_stage2=False,
26    spt_linear_s_stage2=0,
27)
28print(result["status"])                      # COMPLETED
29print(result.get("output"))                  # model output (e.g. media URL)
30print(result["metrics"]["inference_time"])   # server compute seconds
31
32# --- Or submit + poll manually (track request_id, control the cadence) ---
33from segmind import SegmindClient, InferenceFailed, InferenceTimeout
34
35client = SegmindClient()                      # reads SEGMIND_API_KEY
36payload = {
37    "image": "https://segmind-resources.s3.amazonaws.com/input/557ae4e3-8057-4668-bf41-ff836d0f73b0-test_upscale_1234142.jpg",
38    "s_cfg": 7.5,
39    "s_churn": 5,
40    "s_noise": 1.003,
41    "upscale": 1,
42    "a_prompt": "Cinematic, High Contrast, ultra HD, hyper detailed.",
43    "min_size": 1024,
44    "n_prompt": "worst quality, low quality, frames, watermark.",
45    "s_stage1": -1,
46    "s_stage2": 1,
47    "edm_steps": 50,
48    "use_llava": True,
49    "linear_CFG": False,
50    "model_name": "SUPIR-v0Q",
51    "color_fix_type": "Wavelet",
52    "spt_linear_CFG": 1,
53    "linear_s_stage2": False,
54    "spt_linear_s_stage2": 0,
55}
56job = client.submit_async("supir", **payload)
57print(job.request_id)                         # available immediately
58try:
59    result = job.wait(timeout=600, interval=1.0)
60except InferenceTimeout as e:
61    print("still running:", e.request_id)
62except InferenceFailed as e:
63    print("failed:", e.detail)