Index Images for Search

Use AI to index your images based on semantic similarity.

To get started with search, you must first add images to the search index. You can add one or more images to the index at a time. You can supply an image either with a publicly accessible URL or by directly sending image bytes. You can send up to 128 images in one API call.

Java

import com.clarifai.grpc.api.*;
import com.clarifai.grpc.api.status.*;

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

MultiInputResponse postInputsResponse = stub.postInputs(
    PostInputsRequest.newBuilder()
        .addInputs(
            Input.newBuilder()
                .setData(
                    Data.newBuilder().setImage(
                        Image.newBuilder()
                            .setUrl("https://samples.clarifai.com/metro-north.jpg")
                            .setAllowDuplicateUrl(true)
                    )
                )
        )
        .addInputs(
            Input.newBuilder()
                .setData(
                    Data.newBuilder().setImage(
                        Image.newBuilder()
                            .setUrl("https://samples.clarifai.com/wedding.jpg")
                            .setAllowDuplicateUrl(true)
                    )
                )
        )
        .addInputs(
            Input.newBuilder()
                .setData(
                    Data.newBuilder().setImage(
                        Image.newBuilder()
                            .setBase64(ByteString.copyFrom(Files.readAllBytes(
                                new File("{YOUR_IMAGE_FILE_LOCATION}").toPath()
                            )))
                    )
                )
        )
        .build()
);

if (postInputsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
    for (Input input : postInputsResponse.getInputsList()) {
        System.out.println("Input " + input.getId() + " status: ");
        System.out.println(input.getStatus() + "\n");
    }

    throw new RuntimeException("Post inputs failed, status: " + postInputsResponse.getStatus());
}

NodeJS

// Insert here the initialization code as outlined on this page:
// https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

const fs = require("fs");
const imageBytes = fs.readFileSync("{YOUR_IMAGE_FILE_LOCATION}");

stub.PostInputs(
    {
        inputs: [
            {
                data: {image: {url: "https://samples.clarifai.com/metro-north.jpg", allow_duplicate_url: true}}
            },
            {
                data: {image: {url: "https://samples.clarifai.com/puppy.jpeg", allow_duplicate_url: true}}
            },
            {
                data: {image: {base64: imageBytes}}
            }
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            for (const input of response.inputs) {
                console.log("Input " + input.id + " status: ");
                console.log(JSON.stringify(input.status, null, 2) + "\n");
            }

            throw new Error("Post inputs failed, status: " + response.status.description);
        }
    }
);

Python

# Insert here the initialization code as outlined on this page:
# https://docs.clarifai.com/api-guide/api-overview/api-clients#client-installation-instructions

with open("{YOUR_IMAGE_FILE_LOCATION}", "rb") as f:
    file_bytes = f.read()

post_inputs_response = stub.PostInputs(
    service_pb2.PostInputsRequest(
        inputs=[
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/metro-north.jpg",
                        allow_duplicate_url=True
                    )
                )
            ),
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        url="https://samples.clarifai.com/wedding.jpg",
                        allow_duplicate_url=True
                    )
                )
            ),
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        base64=file_bytes
                    )
                )
            ),
        ]
    ),
    metadata=metadata
)

if post_inputs_response.status.code != status_code_pb2.SUCCESS:
    print("There was an error with your request!")
    for input_response in post_inputs_response.inputs:
        print("Input " + input_response.id + " status:")
        print(input_response.status)
    
    print("\tCode: {}".format(post_inputs_response.outputs[0].status.code))
    print("\tDescription: {}".format(post_inputs_response.outputs[0].status.description))
    print("\tDetails: {}".format(post_inputs_response.outputs[0].status.details))
    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

cURL

curl -X POST \
  -H "Authorization: Key YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '
  {
    "inputs": [
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/metro-north.jpg",
            "allow_duplicate_url": true
          }
        }
      },
      {
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/wedding.jpg",
            "allow_duplicate_url": true
          }
        }
      }
    ]
  }'\
  https://api.clarifai.com/v2/inputs

# Use image's "base64" field to upload image from your local machine.

Javascript (REST)

const raw = JSON.stringify({
  "user_app_id": {
		"user_id": "{YOUR_USER_ID}",
		"app_id": "{YOUR_APP_ID}"
	},
  "inputs": [
    {
      "data": {
        "image": {
          "url": "https://samples.clarifai.com/metro-north.jpg",
          "allow_duplicate_url": true
        }
      }
    },
    {
      "data": {
        "image": {
          "url": "https://samples.clarifai.com/wedding.jpg",
          "allow_duplicate_url": true
        }
      }
    }
  ]
});

// # Use image's "base64" field to upload image from your local machine.

const requestOptions = {
  method: 'POST',
  headers: {
    'Accept': 'application/json',
    'Authorization': 'Key {YOUR_PERSONAL_TOKEN}'
  },
	body: raw
};

fetch(`https://api.clarifai.com/v2/inputs`, requestOptions)
  .then(response => response.text())
  .then(result => console.log(result))
  .catch(error => console.log('error', error));

Response JSON

{
  "status": {
    "code": 10000,
    "description": "Ok"
  },
  "inputs": [
    {
      "id": "edc70c917475499abdc7151f41d6cf3e",
      "created_at": "2016-11-22T17:06:02Z",
      "data": {
        "image": {
          "url": "https://samples.clarifai.com/metro-north.jpg"
        }
      },
      "status": {
        "code": 30001,
        "description": "Download pending"
      }
    },
    {
      "id": "f96ca3bbf02041c59addcc13e3468b7d",
      "created_at": "2016-11-22T17:06:02Z",
      "data": {
        "image": {
          "url": "https://samples.clarifai.com/wedding.jpg"
        }
      },
      "status": {
        "code": 30001,
        "description": "Download pending"
      }
    }
  ]
}