POST
javascript
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 const axios = require('axios'); const fs = require('fs'); const path = require('path'); async function toB64(imgPath) { const data = fs.readFileSync(path.resolve(imgPath)); return Buffer.from(data).toString('base64'); } const api_key = "YOUR API-KEY"; const url = "https://api.segmind.com/v1/sam-v2-image"; const data = { "base64": false, "image": toB64('https://segmind-sd-models.s3.amazonaws.com/display_images/sam-v2-ip.jpg'), "overlay_mask": true, "prompt": "boy" }; (async function() { try { const response = await axios.post(url, data, { headers: { 'x-api-key': api_key } }); console.log(response.data); } catch (error) { console.error('Error:', error.response.data); } })();
RESPONSE
image/jpeg
HTTP Response Codes
200 - OKImage Generated
401 - UnauthorizedUser authentication failed
404 - Not FoundThe requested URL does not exist
405 - Method Not AllowedThe requested HTTP method is not allowed
406 - Not AcceptableNot enough credits
500 - Server ErrorServer had some issue with processing

Attributes


base64bool ( default: 1 )

Output as base64 encoded string


coordinatesstr ( default: 1 )

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], ...].


imageimage *

Input image


overlay_maskbool ( default: true )

Whether to overlay a mask on the image


promptstr *

Text prompt for object selection


remove_coordinatesstr ( default: 1 )

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

To keep track of your credit usage, you can inspect the response headers of each API call. The x-remaining-credits property will indicate the number of remaining credits in your account. Ensure you monitor this value to avoid any disruptions in your API usage.

SAM v2 Image

SAM v2 Image (Segmentation Anything Model 2) represents a significant advancement in the field of computer vision, specifically addressing promptable visual segmentation in images. Developed by Meta AI, SAM v2 builds upon its predecessor, SAM, to provide robust and efficient solutions for segmenting objects in diverse visual contexts.

Model Information

  • Architecture: SAM v2 extends the original SAM model, incorporating innovations for image processing.

  • Promptable Segmentation: SAM v2 accepts various prompts (points, boxes, or masks) to identify and segment objects in images.

How to Use the Model

  1. Upload an image (JPG, PNG, or WebP) using the provided field.

  2. Coordinates for selecting objects in an image: Optionally, input coordinates (if needed). 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], ...].

  3. Adjust advanced parameters:

    • Overlay Mask: Decide whether to overlay a mask on the image.

    • Remove Coordinates: If necessary, remove specific coordinates.

  4. Click “Generate” to obtain the segmented image.

Use Cases

  • Assisted Image Labeling: SAM v2 assists in recommending annotations for images during labeling tasks.

  • Augmented Reality (AR) and Virtual Reality (VR): Accurate segmentation enhances realism in AR and VR applications.

  • Sonar Imaging: SAM v2 can be applied to underwater sonar images for object segmentation.

  • Autonomous Vehicles: Real-time segmentation aids in object detection for autonomous driving.

  • Environmental Monitoring: Use SAM v2 to segment objects in satellite imagery for environmental analysis.