Image Superimpose 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    "superimpose-v2",
 9    base_image="https://segmind-sd-models.s3.amazonaws.com/display_images/superimpose-v2-model.jpeg",
10    overlay_image="https://segmind-sd-models.s3.amazonaws.com/display_images/tshirt-logo-2.png",
11    rescale_factor=0.4,
12    resize_method="nearest",
13    bg_remove_model="Bria",
14    blend_mode="screen",
15    opacity=90,
16    x_percent=50,
17    y_percent=65,
18    rotation=0,
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    "base_image": "https://segmind-sd-models.s3.amazonaws.com/display_images/superimpose-v2-model.jpeg",
31    "overlay_image": "https://segmind-sd-models.s3.amazonaws.com/display_images/tshirt-logo-2.png",
32    "rescale_factor": 0.4,
33    "resize_method": "nearest",
34    "bg_remove_model": "Bria",
35    "blend_mode": "screen",
36    "opacity": 90,
37    "x_percent": 50,
38    "y_percent": 65,
39    "rotation": 0,
40    "base64": False,
41}
42job = client.submit_async("superimpose-v2", **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)