Segmind Relighting V2 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    "segmind-relighting-v2",
 9    image="https://segmind-resources.s3.amazonaws.com/output/b9b4e651-ecfb-4dd8-a121-6663f63cca8e-5e23ecbb-6875-4296-9b05-481c03eac5bf.png",
10    light_direction="back",
11    light_type="spotlight",
12    light_temperature="warm",
13    light_intensity="strong",
14    size="auto",
15    quality="high",
16    background="opaque",
17    output_compression=100,
18    output_format="png",
19)
20print(result["status"])                      # COMPLETED
21print(result.get("output"))                  # model output (e.g. media URL)
22print(result["metrics"]["inference_time"])   # server compute seconds
23
24# --- Or submit + poll manually (track request_id, control the cadence) ---
25from segmind import SegmindClient, InferenceFailed, InferenceTimeout
26
27client = SegmindClient()                      # reads SEGMIND_API_KEY
28payload = {
29    "image": "https://segmind-resources.s3.amazonaws.com/output/b9b4e651-ecfb-4dd8-a121-6663f63cca8e-5e23ecbb-6875-4296-9b05-481c03eac5bf.png",
30    "light_direction": "back",
31    "light_type": "spotlight",
32    "light_temperature": "warm",
33    "light_intensity": "strong",
34    "size": "auto",
35    "quality": "high",
36    "background": "opaque",
37    "output_compression": 100,
38    "output_format": "png",
39}
40job = client.submit_async("segmind-relighting-v2", **payload)
41print(job.request_id)                         # available immediately
42try:
43    result = job.wait(timeout=600, interval=1.0)
44except InferenceTimeout as e:
45    print("still running:", e.request_id)
46except InferenceFailed as e:
47    print("failed:", e.detail)