Index Images for Search

// 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);
        }
    }
);

# 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:
    for input_response in post_inputs_response.inputs:
        print("Input " + input_response.id + " status:")
        print(input_response.status)
​
    raise Exception("Post inputs failed, status: " + post_inputs_response.status.description)

app.inputs.create([
  {url: "https://samples.clarifai.com/metro-north.jpg"},
  {url: "https://samples.clarifai.com/wedding.jpg"},
  {base64: "G7p3m95uAl..."}
]).then(
​
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp
from clarifai.rest import Image as ClImage
​
app = ClarifaiApp(api_key='YOUR_API_KEY')
​
img1 = ClImage(url="https://samples.clarifai.com/metro-north.jpg")
img2 = ClImage(url="https://samples.clarifai.com/puppy.jpeg")
img3 = ClImage(file_obj=open('/home/user/image.jpeg', 'rb'))
​
app.inputs.bulk_create_images([img1, img2, img3])

client.addInputs()
    .plus(
        ClarifaiInput.forImage("https://samples.clarifai.com/metro-north.jpg"),
        ClarifaiInput.forImage("https://samples.clarifai.com/wedding.jpg")
    )
    .executeSync();

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Inputs;
​
namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");
​
            await client.AddInputs(
                new ClarifaiURLImage("https://samples.clarifai.com/metro-north.jpg"),
                new ClarifaiURLImage("https://samples.clarifai.com/wedding.jpg")
            ).ExecuteAsync();
        }
    }
}

ClarifaiImage *image1 = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/metro-north.jpg"];
ClarifaiImage *image2 = [[ClarifaiImage alloc] initWithURL:@"https://samples.clarifai.com/wedding.jpg"];
​
[app addInputs:@[image1, image2] completion:^(NSArray<ClarifaiInput *> *inputs, NSError *error) {
    NSLog(@"inputs: %@", inputs);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Inputs\ClarifaiURLImage;
​
$client = new ClarifaiClient('YOUR_API_KEY');
​
$response = $client->addInputs([
    new ClarifaiURLImage('https://samples.clarifai.com/metro-north.jpg'),
    new ClarifaiURLImage('https://samples.clarifai.com/wedding.jpg'),
])->executeSync();
​
if ($response-> isSuccessful()) {
    echo "Response is successful.\n";
} else {
    echo "Response is not successful. Reason: \n";
    echo $response->status()->description() . "\n";
    echo $response->status()->errorDetails() . "\n";
    echo "Status code: " . $response->status()->statusCode();
}

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.