models facebook sam vit base

facebook-sam-vit-base

Overview

The Segment Anything Model (SAM) is an innovative image segmentation tool capable of creating high-quality object masks from simple input prompts. Trained on a massive dataset comprising 11 million images and 1.1 billion masks, SAM demonstrates strong zero-shot capabilities, effectively adapting to new image segmentation tasks without prior specific training. The model's impressive performance matches or exceeds prior models that operated under full supervision.

The above summary was generated using ChatGPT. Review the original-model-card to understand the data used to train the model, evaluation metrics, license, intended uses, limitations and bias before using the model.

Inference samples

Inference type	Python sample (Notebook)	CLI with YAML
Real time	mask-generation-online-endpoint.ipynb	mask-generation-online-endpoint.sh
Batch	mask-generation-batch-endpoint.ipynb	mask-generation-batch-endpoint.sh

Sample inputs and outputs (for real-time inference)

Sample input

{
  "input_data": {
    "columns": [
      "image",
      "input_points",
      "input_boxes",
      "input_labels",
      "multimask_output"
    ],
    "index": [0],
    "data": [["image1", "", "[[650, 900, 1000, 1250]]", "", false]]
  },
  "params": {}
}

Note: "image1" string should be in base64 format or publicly accessible urls.

Sample output

[
    {
        "predictions": [
          0: {
            "mask_per_prediction": [
              0: {
                "encoded_binary_mask": "encoded_binary_mask1",
                "iou_score": 0.85
              }
            ]
          }
        ]
    },
]

Note: "encoded_binary_mask1" string is in base64 format.

Model inference - visualization for a sample image

Version: 1

Tags

Preview license : apache-2.0 task : image-segmentation

View in Studio: https://ml.azure.com/registries/azureml/models/facebook-sam-vit-base/version/1

License: apache-2.0

Properties

SHA: b5fc59950038394bae73f549a55a9b46bc6f3d96

datasets: SA-1B

inference-min-sku-spec: 4|0|32|64

inference-recommended-sku: Standard_DS5_v2, Standard_D8a_v4, Standard_D8as_v4, Standard_D16a_v4, Standard_D16as_v4, Standard_D32a_v4, Standard_D32as_v4, Standard_D48a_v4, Standard_D48as_v4, Standard_D64a_v4, Standard_D64as_v4, Standard_D96a_v4, Standard_D96as_v4, Standard_FX4mds, Standard_F8s_v2, Standard_FX12mds, Standard_F16s_v2, Standard_F32s_v2, Standard_F48s_v2, Standard_F64s_v2, Standard_F72s_v2, Standard_FX24mds, Standard_FX36mds, Standard_FX48mds, Standard_E4s_v3, Standard_E8s_v3, Standard_E16s_v3, Standard_E32s_v3, Standard_E48s_v3, Standard_E64s_v3, Standard_NC4as_T4_v3, Standard_NC6s_v3, Standard_NC8as_T4_v3, Standard_NC12s_v3, Standard_NC16as_T4_v3, Standard_NC24s_v3, Standard_NC64as_T4_v3, Standard_NC24ads_A100_v4, Standard_NC48ads_A100_v4, Standard_NC96ads_A100_v4, Standard_ND96asr_v4, Standard_ND96amsr_A100_v4, Standard_ND40rs_v2

model_id: facebook/sam-vit-base