Qwen Image Edit Plus Product Photography 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    "qwen-image-edit-plus-product-photography",
 9    prompt="Convert the white background image to a scene and place the sofa in the picture in a modern living room",
10    image_1="https://segmind-resources.s3.amazonaws.com/input/8e3e4da5-f25b-49df-ba41-048b279a9f62-10_ELlaximag.webp",
11    lora="product_photography",
12    aspect_ratio="match_input_image",
13    seed=87568756,
14    image_format="webp",
15    quality=95,
16    base64=False,
17)
18print(result["status"])                      # COMPLETED
19print(result.get("output"))                  # model output (e.g. media URL)
20print(result["metrics"]["inference_time"])   # server compute seconds
21
22# --- Or submit + poll manually (track request_id, control the cadence) ---
23from segmind import SegmindClient, InferenceFailed, InferenceTimeout
24
25client = SegmindClient()                      # reads SEGMIND_API_KEY
26payload = {
27    "prompt": "Convert the white background image to a scene and place the sofa in the picture in a modern living room",
28    "image_1": "https://segmind-resources.s3.amazonaws.com/input/8e3e4da5-f25b-49df-ba41-048b279a9f62-10_ELlaximag.webp",
29    "lora": "product_photography",
30    "aspect_ratio": "match_input_image",
31    "seed": 87568756,
32    "image_format": "webp",
33    "quality": 95,
34    "base64": False,
35}
36job = client.submit_async("qwen-image-edit-plus-product-photography", **payload)
37print(job.request_id)                         # available immediately
38try:
39    result = job.wait(timeout=600, interval=1.0)
40except InferenceTimeout as e:
41    print("still running:", e.request_id)
42except InferenceFailed as e:
43    print("failed:", e.detail)