face-to-many Serverless API
Turn a face into 3D, emoji, pixel art, video game, claymation or toy
POST /v2/face-to-many · submit + poll 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 "face-to-many",
9 image="https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg",
10 prompt="a person",
11 style="3D",
12)
13print(result["status"]) # COMPLETED
14print(result.get("output")) # model output (e.g. media URL)
15print(result["metrics"]["inference_time"]) # server compute seconds
16
17# --- Or submit + poll manually (track request_id, control the cadence) ---
18from segmind import SegmindClient, InferenceFailed, InferenceTimeout
19
20client = SegmindClient() # reads SEGMIND_API_KEY
21payload = {
22 "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg",
23 "prompt": "a person",
24 "style": "3D",
25}
26job = client.submit_async("face-to-many", **payload)
27print(job.request_id) # available immediately
28try:
29 result = job.wait(timeout=600, interval=1.0)
30except InferenceTimeout as e:
31 print("still running:", e.request_id)
32except InferenceFailed as e:
33 print("failed:", e.detail) 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 "face-to-many",
9 image="https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg",
10 prompt="a person",
11 style="3D",
12)
13print(result["status"]) # COMPLETED
14print(result.get("output")) # model output (e.g. media URL)
15print(result["metrics"]["inference_time"]) # server compute seconds
16
17# --- Or submit + poll manually (track request_id, control the cadence) ---
18from segmind import SegmindClient, InferenceFailed, InferenceTimeout
19
20client = SegmindClient() # reads SEGMIND_API_KEY
21payload = {
22 "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg",
23 "prompt": "a person",
24 "style": "3D",
25}
26job = client.submit_async("face-to-many", **payload)
27print(job.request_id) # available immediately
28try:
29 result = job.wait(timeout=600, interval=1.0)
30except InferenceTimeout as e:
31 print("still running:", e.request_id)
32except InferenceFailed as e:
33 print("failed:", e.detail)API Endpoint
https://api.segmind.com/v1/face-to-manyParameters
control_depth_strengthoptionalnumberStrength of the depth ControlNet. Higher values increase its influence on the output.
0.8Range: 0 - 1custom_lora_urloptionalstringURL to a Replicate custom LoRA (https://replicate.delivery/pbxt/[id]/trained_model.tar).
""denoising_strengthoptionalnumberHow much of the original image to keep. 1 fully replaces the original, 0 keeps it unchanged.
0.65Range: 0 - 1imageoptionalstring (uri)An image of a person to convert.
"https://segmind-sd-models.s3.amazonaws.com/display_images/Ftm_ip.png.jpg"instant_id_strengthoptionalnumberHow strongly facial identity is preserved.
1Range: 0 - 1lora_scaleoptionalnumberHow strongly the LoRA is applied.
1Range: 0 - 1negative_promptoptionalstringThings to avoid in the generated image.
""promptoptionalstringDescribe the desired output.
"a person"prompt_strengthoptionalnumberCFG scale. Higher values follow the prompt more strongly; lower values keep more likeness to the original image.
4.5Range: 0 - 20seedoptionalintegerSeed for reproducible results. -1 randomizes on every request.
-1Range: -1 - 999999999999999styleoptionalstringThe style to convert the image into.
"3D""3D""Emoji""Video game""Pixels""Clay""Toy"Response Type
Returns: Image
Asynchronous requests (v2)
Use Async for video, long-running (>~60s), or high-concurrency workloads; Sync is simplest for fast image & LLM calls. Async submits a request and you poll it to completion.
- 1
POST /v2/face-to-manySubmit — returns request_id, status_url, response_url
- 2
GET /v2/requests/{id}/statusPoll — until COMPLETED or FAILED
- 3
GET /v2/requests/{id}Result — final response body
Status states
- A FAILED request is served as HTTP 422 — the body still carries the error detail.
- An unknown or expired request_id returns HTTP 404.
- Results are retained for 1 hour, then expire.
- Content / RAI blocks surface as FAILED, not a separate state.
- Track completion by polling the status endpoint.
Common Error Codes
The API returns standard HTTP status codes. Detailed error messages are provided in the response body.
Bad Request
Invalid parameters or request format
Unauthorized
Missing or invalid API key
Forbidden
Insufficient permissions
Not Found
Model or endpoint not found
Insufficient Credits
Not enough credits to process request
Rate Limited
Too many requests
Server Error
Internal server error
Bad Gateway
Service temporarily unavailable
Timeout
Request timed out