Bria Enhance Image 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    "bria-enhance-image",
 9    image="https://segmind-resources.s3.amazonaws.com/input/a53c2a29-1e2c-473b-ad5a-2dfdb1184dfa-e8a1673f-7919-463e-b6fb-e12ad39140f1.jpeg",
10    visual_input_content_moderation=True,
11    visual_output_content_moderation=True,
12    seed=123456,
13    steps_num=30,
14    resolution="4MP",
15    preserve_alpha=True,
16)
17print(result["status"])                      # COMPLETED
18print(result.get("output"))                  # model output (e.g. media URL)
19print(result["metrics"]["inference_time"])   # server compute seconds
20
21# --- Or submit + poll manually (track request_id, control the cadence) ---
22from segmind import SegmindClient, InferenceFailed, InferenceTimeout
23
24client = SegmindClient()                      # reads SEGMIND_API_KEY
25payload = {
26    "image": "https://segmind-resources.s3.amazonaws.com/input/a53c2a29-1e2c-473b-ad5a-2dfdb1184dfa-e8a1673f-7919-463e-b6fb-e12ad39140f1.jpeg",
27    "visual_input_content_moderation": True,
28    "visual_output_content_moderation": True,
29    "seed": 123456,
30    "steps_num": 30,
31    "resolution": "4MP",
32    "preserve_alpha": True,
33}
34job = client.submit_async("bria-enhance-image", **payload)
35print(job.request_id)                         # available immediately
36try:
37    result = job.wait(timeout=600, interval=1.0)
38except InferenceTimeout as e:
39    print("still running:", e.request_id)
40except InferenceFailed as e:
41    print("failed:", e.detail)