Segmind SceneCraft v0.1 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-scenecraft-v01",
 9    image="https://segmind-resources.s3.amazonaws.com/input/ea6c55f7-f97d-49e4-964f-09cfd27082f5-sofa_WSFABLZPN3FRAB_2.png",
10    prompt="Create a close-up and mid-range product shot of a modern living room sofa with a matte fabric texture and detailed stitching. The scene is set in a warm, cozy living space with soft ambient lighting coming from a side window filtered through sheer linen curtains. Accentuate the sofa’s contours with gentle, natural shadows and subtle reflections on nearby decor elements like a coffee table and floor lamp. Use a color palette dominated by earthy tones — warm beige, soft greys, and muted olive — to create a harmonious and inviting atmosphere. Include a minimalistic rug, wooden flooring, and a few aesthetic accessories like throw pillows and a blanket to enhance lifestyle appeal. Emphasize depth of field for a realistic photographic finish.",
11    negative_prompt="blur, CGI, animated",
12    seed=-1,
13    steps=40,
14    guidance_scale=7,
15    x_value=50,
16    y_value=50,
17    scale=0.65,
18    megapixel="1.5",
19    aspect_ratio="16:9 (Panorama)",
20    dropshadow=True,
21    upscale=False,
22    image_format="jpeg",
23    image_quality=90,
24)
25print(result["status"])                      # COMPLETED
26print(result.get("output"))                  # model output (e.g. media URL)
27print(result["metrics"]["inference_time"])   # server compute seconds
28
29# --- Or submit + poll manually (track request_id, control the cadence) ---
30from segmind import SegmindClient, InferenceFailed, InferenceTimeout
31
32client = SegmindClient()                      # reads SEGMIND_API_KEY
33payload = {
34    "image": "https://segmind-resources.s3.amazonaws.com/input/ea6c55f7-f97d-49e4-964f-09cfd27082f5-sofa_WSFABLZPN3FRAB_2.png",
35    "prompt": "Create a close-up and mid-range product shot of a modern living room sofa with a matte fabric texture and detailed stitching. The scene is set in a warm, cozy living space with soft ambient lighting coming from a side window filtered through sheer linen curtains. Accentuate the sofa’s contours with gentle, natural shadows and subtle reflections on nearby decor elements like a coffee table and floor lamp. Use a color palette dominated by earthy tones — warm beige, soft greys, and muted olive — to create a harmonious and inviting atmosphere. Include a minimalistic rug, wooden flooring, and a few aesthetic accessories like throw pillows and a blanket to enhance lifestyle appeal. Emphasize depth of field for a realistic photographic finish.",
36    "negative_prompt": "blur, CGI, animated",
37    "seed": -1,
38    "steps": 40,
39    "guidance_scale": 7,
40    "x_value": 50,
41    "y_value": 50,
42    "scale": 0.65,
43    "megapixel": "1.5",
44    "aspect_ratio": "16:9 (Panorama)",
45    "dropshadow": True,
46    "upscale": False,
47    "image_format": "jpeg",
48    "image_quality": 90,
49}
50job = client.submit_async("segmind-scenecraft-v01", **payload)
51print(job.request_id)                         # available immediately
52try:
53    result = job.wait(timeout=600, interval=1.0)
54except InferenceTimeout as e:
55    print("still running:", e.request_id)
56except InferenceFailed as e:
57    print("failed:", e.detail)