Rank

Rank Order your search results with the intuitive insights of AI. Your model can identify concepts in your data and rank your search results by how confident it is that a given concept is present. You can even rank search results by how similar one input is to another input.

Search By Concept

Once your images are indexed, you can search for them by concept.

app.inputs.search({ concept: {name: 'people'} }).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

# search by public concept
app.inputs.search_by_predicted_concepts(concept='people')

# search by a list of concepts
app.inputs.search_by_predicted_concepts(concepts=['people'])

# search by concept id
app.inputs.search_by_predicted_concepts(concept_id='ai_dP13sXL4')

# search by a list of concept ids
app.inputs.search_by_predicted_concepts(concept_ids=['ai_dP13sXL4'])

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.SearchInputs(SearchBy.ConceptName("people"))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

// First create a search term with a concept you want to search.
ClarifaiConcept *conceptFromGeneralModel = [[ClarifaiConcept alloc] initWithConceptName:@"people"];
ClarifaiSearchTerm *searchTerm = [ClarifaiSearchTerm searchByPredictedConcept:conceptFromGeneralModel];

[app search:@[searchTerm] page:@1 perPage:@20 completion:^(NSArray<ClarifaiSearchResult *> *results, NSError *error) {
  // Print output of first search result.
  NSLog(@"inputID: %@", results[0].inputID);
  NSLog(@"URL: %@", results[0].mediaURL);
  NSLog(@"probability of public concept: %@", results[0].score);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->searchInputs(SearchBy::conceptName('people'))->executeSync();

if ($response-> isSuccessful()) {

    /** @var SearchInputsResult $result */
    $result = $response->get();
    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '
  {
    "query": {
      "ands": [
        {
          "output": {
            "data": {
              "concepts": [
                {
                  "name": "people"
                }
              ]
            }
          }
        }
      ]
    }
  }'\
  https://api.clarifai.com/v2/searches

{
  "status": {
    "code": 10000,
    "description": "Ok"
  },
  "id":"d275a3c0f3e748378617d6ba9bd0f8d4",
  "hits": [
    {
      "score": 0.98155165,
      "input": {
        "id": "f96ca3bbf02041c59addcc13e3468b7d",
        "created_at": "2016-11-22T17:06:02Z",
        "data": {
          "image": {
            "url": "https://samples.clarifai.com/wedding.jpg"
          }
        },
        "status": {
          "code": 30000,
          "description": "Download complete"
        }
      }
    }
  ]
}

By Public Concepts

When you add an input, it automatically gets predictions from the general model. You can search for those predictions.

app.inputs.search([
  {
    concept: {
      name: 'cat'
    }
  },
  {
    concept: {
      name: 'dog'
    }
  }
]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_CLARIFAI_KEY')

# search by single concept name
app.inputs.search_by_predicted_concepts(concept='cat')

# search by single concept id
app.inputs.search_by_predicted_concepts(concept_id='ai_mFqxrph2')

# search by multiple concepts with name
app.inputs.search_by_predicted_concepts(concepts=['cat', 'cute'])

# search by multiple concepts with ids
app.inputs.search_by_predicted_concepts(concept_ids=['ai_mFqxrph2', 'ai_4CRlSvbV'])

# search by multiple concepts with not logic
app.inputs.search_by_predicted_concepts(concepts=['cat', 'dog'], values=[True, False])

// Search concept by name
client.searchInputs(SearchClause.matchConcept(Concept.forName("cat")))
    .getPage(1)
    .executeSync();

// Search concept by ID
client.searchInputs(SearchClause.matchConcept(Concept.forID("ai_mFqxrph2")))
    .getPage(1)
    .executeSync();

// Search multiple concepts
client.searchInputs(SearchClause.matchConcept(Concept.forID("cat")))
    .and(SearchClause.matchConcept(Concept.forID("cute")))
    .getPage(1)
    .executeSync();

// Search NOT by concept
client.searchInputs(SearchClause.matchConcept(Concept.forID("cat").withValue(false)))
    .getPage(1)
    .executeSync();

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            // Search concept by name
            await client.SearchInputs(SearchBy.ConceptName("cat"))
                .Page(1)
                .ExecuteAsync();

            // Search concept by ID
            await client.SearchInputs(SearchBy.ConceptID("cat"))
                .Page(1)
                .ExecuteAsync();

            // Search multiple concepts
            await client.SearchInputs(
                    SearchBy.ConceptID("cat"),
                    SearchBy.ConceptID("cute"))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

// First create a search term with a concept you want to search.
ClarifaiConcept *conceptFromGeneralModel = [[ClarifaiConcept alloc] initWithConceptName:@"fast"];
ClarifaiSearchTerm *searchTerm = [ClarifaiSearchTerm searchByPredictedConcept:conceptFromGeneralModel];

[app search:@[searchTerm] page:@1 perPage:@20 completion:^(NSArray<ClarifaiSearchResult *> *results, NSError *error) {
  // Print output of first search result.
  NSLog(@"inputID: %@", results[0].inputID);
  NSLog(@"URL: %@", results[0].mediaURL);
  NSLog(@"probability of input matching search query: %@", results[0].score);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

// Search concept by name
$response = $client->searchInputs(SearchBy::conceptName('cat'))
    ->executeSync();

/*
// Search concept by ID
$response = $client->searchInputs(SearchBy::conceptID('cat'))
    ->executeSync();
*/

/*
// Search multiple concepts
$response = $client->searchInputs([SearchBy::conceptID('cat'), SearchBy::conceptID('cute')])
    ->executeSync();
*/

if ($response->isSuccessful()) {
    echo "Response is successful.\n";

    /** @var SearchInputsResult $result */
    $result = $response->get();

    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '
  {
    "query": {
      "ands": [
        {
          "output": {
            "data": {
              "concepts": [
                {
                  "name":"dog"
                }
              ]
            }
          }
        }
      ]
    }
  }'\
  https://api.clarifai.com/v2/searches

By Custom Concepts

After you have added inputs with concepts, you can search by those concepts.

app.inputs.search([
  {
    concept: {
      type: 'input',
      name: 'cat'
    }
  },
  {
    concept: {
      type: 'input',
      name: 'dog'
    }
  }
]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_CLARIFAI_KEY')

# search by single concept name
app.inputs.search_by_annotated_concepts(concept='cat')

# search by single concept id
app.inputs.search_by_annotated_concepts(concept_id='ai_mFqxrph2')

# search by multiple concepts with name
app.inputs.search_by_annotated_concepts(concepts=['cat', 'cute'])

# search by multiple concepts with ids
app.inputs.search_by_annotated_concepts(concept_ids=['ai_mFqxrph2', 'ai_4CRlSvbV'])

# search by multiple concepts with not logic
app.inputs.search_by_annotated_concepts(concepts=['cat', 'dog'], values=[True, False])

// Search concept by name
client.searchInputs(SearchClause.matchUserTaggedConcept(Concept.forName("cat")))
    .getPage(1)
    .executeSync();

// Search concept by ID
client.searchInputs(SearchClause.matchUserTaggedConcept(Concept.forID("ai_mFqxrph2")))
    .getPage(1)
    .executeSync();

// Search multiple concepts
client.searchInputs(SearchClause.matchUserTaggedConcept(Concept.forID("cat")))
    .and(SearchClause.matchUserTaggedConcept(Concept.forID("cute")))
    .getPage(1)
    .executeSync();

// Search NOT by concept
client.searchInputs(SearchClause.matchUserTaggedConcept(Concept.forID("cat").withValue(false)))
    .getPage(1)
    .executeSync();

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            // Search concept by name
            await client.SearchInputs(SearchBy.UserTaggedConceptName("cat")
                )
                .Page(1)
                .ExecuteAsync();

            // Search concept by ID
            await client.SearchInputs(SearchBy.UserTaggedConceptID("ai_mFqxrph2")
                )
                .Page(1)
                .ExecuteAsync();

            // Search multiple concepts
            await client.SearchInputs(
                    SearchBy.UserTaggedConceptID("cat"),
                    SearchBy.UserTaggedConceptID("cute"))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

// If you have previously added inputs tagged with "dog", you can search for them by the same tag.
ClarifaiConcept *concept = [[ClarifaiConcept alloc] initWithConceptName:@"dog"];
ClarifaiSearchTerm *term = [ClarifaiSearchTerm searchInputsByConcept:concept];

[app search:@[term] page:@1 perPage:@20 completion:^(NSArray<ClarifaiSearchResult *> *results, NSError *error) {
  // Print output of first search result.
  NSLog(@"inputID: %@", results[0].inputID);
  NSLog(@"URL: %@", results[0].mediaURL);
  NSLog(@"probability of input matching search query: %@", results[0].score);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

// Search concept by name
$response = $client->searchInputs(SearchBy::userTaggedConceptName('cat'))
    ->executeSync();

/*
// Search concept by ID
$response = $client->searchInputs(SearchBy::userTaggedConceptID('cat'))
    ->executeSync();
*/

/*
// Search multiple concepts
$response = $client->searchInputs([SearchBy::userTaggedConceptName('cat'),
        SearchBy::userTaggedConceptID('dog')])
    ->executeSync();
*/

if ($response->isSuccessful()) {
    echo "Response is successful.\n";

    /** @var SearchInputsResult $result */
    $result = $response->get();

    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '
  {
    "query": {
      "ands": [
        {
          "input": {
            "data": {
              "concepts": [
                {
                  "name":"dog"
                }
              ]
            }
          }
        }
      ]
    }
  }'\
  https://api.clarifai.com/v2/searches

By public and custom concepts

You can combine a search to find inputs that have concepts you have supplied as well as predictions from your model.

app.inputs.search([
  // this is the public concept
  {
    concept: {
      name: 'cat'
    }
  },
  // this is the user-supplied concept
  {
    concept: {
      type: 'input',
      name: 'dog'
    }
  }
]).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp, InputSearchTerm, OutputSearchTerm, SearchQueryBuilder
app = ClarifaiApp(api_key='YOUR_API_KEY')

term1 = InputSearchTerm(concept='cat')
term2 = OutputSearchTerm(concept='dog', value=False)
query = SearchQueryBuilder()
query.add_term(term1)
query.add_term(term2)

app.inputs.search(query)

client.searchInputs()
    // Matches images we tagged as "cat", and that the API tagged as not having "dog"
    .ands(
        SearchClause.matchUserTaggedConcept(Concept.forName("cat")),
        SearchClause.matchConcept(Concept.forName("dog").withValue(false))
    )
    .getPage(1)
    .executeSync();

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.SearchInputs(
                    SearchBy.UserTaggedConceptName("cat"),
                    SearchBy.ConceptID("dog"))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

ClarifaiConcept *conceptFromGeneralModel = [[ClarifaiConcept alloc] initWithConceptName:@"fast"];
ClarifaiConcept *conceptFromTrainedCustomModel = [[ClarifaiConcept alloc] initWithConceptName:@"dog"];

ClarifaiSearchTerm *term1 = [ClarifaiSearchTerm searchByPredictedConcept:conceptFromGeneralModel];
ClarifaiSearchTerm *term2 = [ClarifaiSearchTerm searchByPredictedConcept:conceptFromTrainedCustomModel];

[_app search:@[term1, term2] page:@1 perPage:@20 completion:^(NSArray<ClarifaiSearchResult *> *results, NSError *error) {
  // Print output of first search result.
  NSLog(@"inputID: %@", results[0].inputID);
  NSLog(@"URL: %@", results[0].mediaURL);
  NSLog(@"probability of input matching search query: %@", results[0].score);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->searchInputs([SearchBy::userTaggedConceptName('cat'),
        SearchBy::conceptID('dog')])
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";

    /** @var SearchInputsResult $result */
    $result = $response->get();

    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '
{
  "query": {
    "ands": [
      {
        "output": {
          "data": {
            "concepts": [
              {
                "name": "fast"
              }
            ]
          }
        }
      },
      {
        "input": {
          "data": {
            "concepts": [
              {
                "name": "ferrari23",
                "value": true
              }
            ]
          }
        }
      }
    ]
  }
}'\
https://api.clarifai.com/v2/searches

By Image

You can use images to search through your collection. The API will return ranked results based on how similar the results are to the image you provided in your query.

app.inputs.search(
  {
    input: {
      url: 'https://samples.clarifai.com/puppy.jpg'
    }
  }
).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_CLARIFAI_KEY')

# search by image url
app.inputs.search_by_image(url="https://samples.clarifai.com/metro-north.jpg")

# search by existing input id
input_id = "some_existing_input_id"
app.inputs.search_by_image(image_id=input_id)

# search by raw bytes
data = "image_raw_bytes"
app.inputs.search_by_image(imgbytes=data)

# search by base64 bytes
base64_data = "image_bytes_encoded_in_base64"
app.inputs.search_by_image(base64bytes=base64_data)

# search by local filename
filename="filename_on_local_disk.jpg"
app.inputs.search_by_image(filename=filename)

# search from fileio
fio = open("filename_on_local_disk.jpg", 'rb')
app.inputs.search_by_image(fileobj=fio)

// Search by image URL (String or java.net.URL)
client.searchInputs(SearchClause.matchImageVisually(ClarifaiImage.of("https://samples.clarifai.com/metro-north.jpg")))
    .getPage(1)
    .executeSync();

// Search by local image (java.io.File or byte[])
client.searchInputs(SearchClause.matchImageVisually(ClarifaiImage.of(new File("image.png"))))
    .getPage(1)
    .executeSync();

using System.IO;
using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            // Search by image URL
            await client.SearchInputs(
                    SearchBy.ImageVisually("https://samples.clarifai.com/metro-north.jpg"))
                .Page(1)
                .ExecuteAsync();

            // Search by local image
            await client.SearchInputs(
                    SearchBy.ImageVisually(File.ReadAllBytes("image.png")))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

ClarifaiSearchTerm *searchTerm = [ClarifaiSearchTerm searchVisuallyWithImageURL:@"https://samples.clarifai.com/metro-north.jpg"];

[app search:@[searchTerm] page:@1 perPage:@20 completion:^(NSArray<ClarifaiSearchResult *> *results, NSError *error) {
  // Print output of first search result.
  NSLog(@"inputID: %@", results[0].inputID);
  NSLog(@"URL: %@", results[0].mediaURL);
  NSLog(@"probability of input matching search query: %@", results[0].score);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->searchInputs(
        SearchBy::urlImageVisually('https://samples.clarifai.com/metro-north.jpg'))
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";

    /** @var SearchInputsResult $result */
    $result = $response->get();

    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '
  {
    "query": {
      "ands": [
        {
          "output":{
            "input":{
              "data": {
                "image": {
                  "url": "https://samples.clarifai.com/metro-north.jpg"
                }
              }
            }
          }
        }
      ]
    }
  }'\
  https://api.clarifai.com/v2/searches

By Url

You can also search for an input by URL.

app.inputs.search(
  {
    input: {
      type: 'input',
      url: 'https://samples.clarifai.com/puppy.jpg'
    }
  }
).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.SearchInputs(
                    SearchBy.ImageURL("https://samples.clarifai.com/metro-north.jpg"))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

// Lookup images with this URL
ClarifaiSearchTerm *term = [ClarifaiSearchTerm searchInputsWithImageURL:@"https://samples.clarifai.com/metro-north.jpg"];

[app search:@[term] page:@1 perPage:@20 completion:^(NSArray<ClarifaiSearchResult *> *results, NSError *error) {
  // Print output of first search result.
  NSLog(@"inputID: %@", results[0].inputID);
  NSLog(@"URL: %@", results[0].mediaURL);
  NSLog(@"probability of input matching search query: %@", results[0].score);
}];

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->searchInputs(
        SearchBy::imageURL('https://samples.clarifai.com/metro-north.jpg'))
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";

    /** @var SearchInputsResult $result */
    $result = $response->get();

    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '
  {
    "query": {
      "ands": [
        {
          "input":{
            "data": {
              "image": {
                "url": "https://samples.clarifai.com/metro-north.jpg"
              }
            }
          }
        }
      ]
    }
  }'\
  https://api.clarifai.com/v2/searches

By Image With Crop

You can search using a crop of an image through your collection. The API will still return ranked results based upon on how similar the results are to the crop of the image you provide in your query.

app.inputs.search(
  {
    input: {
      url: 'https://samples.clarifai.com/puppy.jpg',
      crop: [0.1, 0.1, 0.9, 0.9]
    }
  }
).then(
  function(response) {
    // do something with response
  },
  function(err) {
    // there was an error
  }
);

from clarifai.rest import ClarifaiApp
app = ClarifaiApp(api_key='YOUR_API_KEY')

search = app.inputs.search_by_image(url='https://samples.clarifai.com/puppy.jpg', crop=[0.1, 0.1, 0.9, 0.9])

print search

client.searchInputs(SearchClause.matchImageVisually(ClarifaiImage.of("https://samples.clarifai.com/puppy.jpg")
    .withCrop(Crop.create()
        .top(0.1F)
        .left(0.1F)
        .bottom(0.9F)
        .right(0.9F)
    )
))
.getPage(1)
.executeSync();

using System.Threading.Tasks;
using Clarifai.API;
using Clarifai.DTOs;
using Clarifai.DTOs.Searches;

namespace YourNamespace
{
    public class YourClassName
    {
        public static async Task Main()
        {
            var client = new ClarifaiClient("YOUR_API_KEY");

            await client.SearchInputs(SearchBy.ImageVisually(
                    "https://samples.clarifai.com/metro-north.jpg",
                    crop: new Crop(0.1M, 0.1M, 0.9M, 0.9M)))
                .Page(1)
                .ExecuteAsync();
        }
    }
}

use Clarifai\API\ClarifaiClient;
use Clarifai\DTOs\Crop;
use Clarifai\DTOs\Searches\SearchBy;
use Clarifai\DTOs\Searches\SearchInputsResult;

$client = new ClarifaiClient('YOUR_API_KEY');

$response = $client->searchInputs(
        SearchBy::urlImageVisually('https://samples.clarifai.com/metro-north.jpg')
            ->withCrop(new Crop(0.1, 0.1, 0.9, 0.9)))
    ->executeSync();

if ($response->isSuccessful()) {
    echo "Response is successful.\n";

    /** @var SearchInputsResult $result */
    $result = $response->get();

    foreach ($result->searchHits() as $searchHit) {
        echo $searchHit->input()->id() . ' ' . $searchHit->score() . "\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 '{
  "query": {
    "ands": [
      {
        "output": {
          "input": {
              "data": {
                "image": {
                    "url": "https://samples.clarifai.com/puppy.jpg",
                    "crop": [0.1,0.1,0.9,0.9]
                }
            }
          }
        }
      }
    ]
  }
}'\
https://api.clarifai.com/v2/searches

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Last updated 5 years ago

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