SAM3
Meta의 SAM3 모델을 Serverless Cloud API를 통해 사용하세요.
개념 분할(PCS)
텍스트 프롬프트
import os
import requests
payload = {
"image": {"type": "url", "value": "https://media.roboflow.com/inference/people-walking.jpg"},
"prompts": [
{"type": "text", "text": "person"},
{"type": "text", "text": "backpack"},
],
"output_prob_thresh": 0.5,
"format": "polygon", # 또는 "rle"
}
response = requests.post(
"https://serverless.roboflow.com/sam3/concept_segment",
params={"api_key": os.environ["ROBOFLOW_API_KEY"]},
json=payload,
)
for prompt_result in response.json()["prompt_results"]:
print(prompt_result["echo"], len(prompt_result["predictions"]), "인스턴스")예시 상자 프롬프트
텍스트 및 예시 결합 프롬프트
시각 분할(PVS)
추론 속도
엔드포인트
Your Roboflow API Key. Get one at https://app.roboflow.com/settings/api
One of 'polygon', 'rle'
polygonOptional ID for caching embeddings.
Score threshold for outputs.
0.5The model ID of SAM3. Use 'sam3/sam3_final' to target the generic base model.
sam3/sam3_finalIoU threshold for cross-prompt NMS. If not set, NMS is disabled. Must be in [0.0, 1.0] when set.
Successful Response
The time in seconds it took to produce the segmentation including preprocessing
Validation Error
POST /sam3/concept_segment?api_key=text HTTP/1.1
Host: serverless.roboflow.com
Content-Type: application/json
Accept: */*
Content-Length: 206
{
"image": {
"type": "url",
"value": "https://media.roboflow.com/notebooks/examples/dog.jpeg"
},
"prompts": [
{
"type": "text",
"text": "person"
},
{
"type": "text",
"text": "car"
}
],
"output_prob_thresh": 0.5,
"format": "polygon"
}{
"prompt_results": [
{
"prompt_index": 0,
"echo": {
"prompt_index": 0,
"type": "text",
"text": "dog",
"num_boxes": 0
},
"predictions": [
{
"masks": [
[
[
345,
251
],
[
344,
252
],
[
343,
253
]
]
],
"confidence": 0.89453125,
"format": "polygon"
}
]
}
],
"time": 0.221
}Your Roboflow API Key. Get one at https://app.roboflow.com/settings/api
SAM2 visual segmentation request.
The ID of the image to be segmented used to retrieve cached embeddings. If an embedding is cached, it will be used instead of generating a new embedding. If no embedding is cached, a new embedding will be generated and cached.
image_idThe format of the response. Must be one of 'json', 'rle', or 'binary'. If binary, masks are returned as binary numpy arrays. If json, masks are converted to polygons. If rle, masks are converted to RLE format.
jsonExample: jsonThe version ID of SAM to be used for this request. Must be one of hiera_tiny, hiera_small, hiera_large, hiera_b_plus
hiera_largeExample: hiera_largeIf true, the model will return three masks. For ambiguous input prompts (such as a single click), this will often produce better masks than a single prediction.
trueExample: trueIf True, saves the low-resolution logits to the cache for potential future use.
falseIf True, attempts to load previously cached low-resolution logits for the given image and prompt set.
falseSuccessful Response
The time in seconds it took to produce the segmentation including preprocessing
Validation Error
POST /sam3/visual_segment?api_key=text HTTP/1.1
Host: serverless.roboflow.com
Content-Type: application/json
Accept: */*
Content-Length: 294
{
"image": {
"type": "url",
"value": "http://www.example-image-url.com"
},
"image_id": "image_id",
"prompts": [
{
"prompts": [
{
"points": [
{
"positive": true,
"x": 100,
"y": 100
}
]
}
]
}
],
"format": "json",
"sam2_version_id": "hiera_large",
"multimask_output": true,
"save_logits_to_cache": false,
"load_logits_from_cache": false
}{
"prompt_results": [
{
"prompt_index": 1,
"predictions": []
}
],
"time": 1
}Inference(자체 호스팅)와 함께 사용
Docker에서 실행
Python에서 모델 로드
Python의 대화형 분할
Workflows에서 사용
동영상 추적
SAM3-3D(베타)
또한 참조
마지막 업데이트
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