Sam3 Image Serverless API
Precise object segmentation and tracking in images.
POST /v2/sam3-image · 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 "sam3-image",
9 image="https://segmind-resources.s3.amazonaws.com/input/6faa9243-e250-424b-b1b9-c5f1e5e93ab9-sample1.jpg",
10 text_prompt="plants",
11 return_preview=True,
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-resources.s3.amazonaws.com/input/6faa9243-e250-424b-b1b9-c5f1e5e93ab9-sample1.jpg",
23 "text_prompt": "plants",
24 "return_preview": True,
25}
26job = client.submit_async("sam3-image", **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 "sam3-image",
9 image="https://segmind-resources.s3.amazonaws.com/input/6faa9243-e250-424b-b1b9-c5f1e5e93ab9-sample1.jpg",
10 text_prompt="plants",
11 return_preview=True,
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-resources.s3.amazonaws.com/input/6faa9243-e250-424b-b1b9-c5f1e5e93ab9-sample1.jpg",
23 "text_prompt": "plants",
24 "return_preview": True,
25}
26job = client.submit_async("sam3-image", **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/sam3-imageParameters
imagerequiredstring (uri)Input image to segment. Use a high-resolution image for better accuracy.
boxes_inputoptionalstringBounding box to specify the object to segment, e.g. "[[100, 150, 200, 250]]".
""max_masksoptionalintegerLimit on the number of masks returned. 0 means no limit.
0Range: 0 - 100point_labels_inputoptionalstringLabels for each point: 1 = foreground, 0 = background.
"[[1]]"points_inputoptionalstringPoint coordinates to specify the object to segment, e.g. "[[300, 400]]" or "[[150, 200], [300, 400]]" for multiple points.
""points_per_sideoptionalintegerDensity for automatic mask creation. Higher values produce finer detail.
32Range: 0 - 128pred_iou_threshoptionalnumberIoU score filter. Higher values enforce stricter mask quality.
0.88Range: 0.5 - 1return_masksoptionalbooleanReturn each detected mask separately.
falsereturn_overlayoptionalbooleanReturn the masks overlaid on the input image, for visual assessment.
falsereturn_previewoptionalbooleanReturn a combined preview mask for a quick results check.
truetext_promptoptionalstringOptional text prompt to guide what the model segments, e.g. "animal", "plant".
""thresholdoptionalnumberConfidence threshold for detection. 0.5 gives balanced results.
0.5Range: 0.1 - 1Response 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/sam3-imageSubmit — 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