Sam V2 Image Serverless API

SAM v2, the next-gen segmentation model from Meta AI, revolutionizes computer vision. Building on SAM's success, it excels at accurately segmenting objects in images, offering robust and efficient solutions for various visual contexts.

~1.70s

Playground API

Pricing

~1.70s

POST /v2/sam-v2-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    "sam-v2-image",
 9    base64=False,
10    image="https://segmind-sd-models.s3.amazonaws.com/display_images/sam-v2-ip.jpg",
11    overlay_mask=True,
12    prompt="boy",
13)
14print(result["status"])                      # COMPLETED
15print(result.get("output"))                  # model output (e.g. media URL)
16print(result["metrics"]["inference_time"])   # server compute seconds
17
18# --- Or submit + poll manually (track request_id, control the cadence) ---
19from segmind import SegmindClient, InferenceFailed, InferenceTimeout
20
21client = SegmindClient()                      # reads SEGMIND_API_KEY
22payload = {
23    "base64": False,
24    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/sam-v2-ip.jpg",
25    "overlay_mask": True,
26    "prompt": "boy",
27}
28job = client.submit_async("sam-v2-image", **payload)
29print(job.request_id)                         # available immediately
30try:
31    result = job.wait(timeout=600, interval=1.0)
32except InferenceTimeout as e:
33    print("still running:", e.request_id)
34except InferenceFailed as e:
35    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    "sam-v2-image",
 9    base64=False,
10    image="https://segmind-sd-models.s3.amazonaws.com/display_images/sam-v2-ip.jpg",
11    overlay_mask=True,
12    prompt="boy",
13)
14print(result["status"])                      # COMPLETED
15print(result.get("output"))                  # model output (e.g. media URL)
16print(result["metrics"]["inference_time"])   # server compute seconds
17
18# --- Or submit + poll manually (track request_id, control the cadence) ---
19from segmind import SegmindClient, InferenceFailed, InferenceTimeout
20
21client = SegmindClient()                      # reads SEGMIND_API_KEY
22payload = {
23    "base64": False,
24    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/sam-v2-ip.jpg",
25    "overlay_mask": True,
26    "prompt": "boy",
27}
28job = client.submit_async("sam-v2-image", **payload)
29print(job.request_id)                         # available immediately
30try:
31    result = job.wait(timeout=600, interval=1.0)
32except InferenceTimeout as e:
33    print("still running:", e.request_id)
34except InferenceFailed as e:
35    print("failed:", e.detail)

API Endpoint

POSThttps://api.segmind.com/v1/sam-v2-image

Parameters

imagerequired

string (uri)

Input image

Default: "https://segmind-sd-models.s3.amazonaws.com/display_images/sam-v2-ip.jpg"

promptrequired

string

Text prompt for object selection

Default: "boy"

base64optional

boolean

Output as base64 encoded string

Default: false

coordinatesoptional

string

Coordinates for image selection (optional): Provide either a prompt or coordinates. If a prompt is provided, coordinates will be ignored. For a single coordinate, use the format [834,74]. For multiple coordinates, use [[839,74], [844,20], ...].

Default: null

overlay_maskoptional

boolean

Whether to overlay a mask on the image

Default: true

remove_coordinatesoptional

string

Coordinates to be removed (optional), format is similar to Coordinates

Default: null

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/sam-v2-image
Submit — returns request_id, status_url, response_url
2
GET /v2/requests/{id}/status
Poll — until COMPLETED or FAILED
3
GET /v2/requests/{id}
Result — final response body

Status states

QUEUED— Accepted, waiting for a worker

PROCESSING— Running on a worker

COMPLETED— Done — result body is ready

FAILED— Errored (incl. content/RAI blocks)

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.

400

Bad Request

Invalid parameters or request format

401

Unauthorized

Missing or invalid API key

403

Forbidden

Insufficient permissions

404

Not Found

Model or endpoint not found

406

Insufficient Credits

Not enough credits to process request

429

Rate Limited

Too many requests

500

Server Error

Internal server error

502

Bad Gateway

Service temporarily unavailable

504

Timeout

Request timed out