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 or region of the input model detected. The search results will return the input but also the annotation which includes the region.

Search By Concepts

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

By clarifai/main App Concepts

When you add an input, it automatically gets predictions from the models in your default which are typically models from the clarifai/main app such as the general model. You can search by those predictions.

gRPC 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

MultiSearchResponse postAnnotationsSearchesResponse = stub.postAnnotationsSearches(
    PostAnnotationsSearchesRequest.newBuilder().addSearches(
        Search.newBuilder().setQuery(
            Query.newBuilder().addRanks(
                Rank.newBuilder().setAnnotation(
                    Annotation.newBuilder().setData(
                            Data.newBuilder().addConcepts(  // You can search by multiple concepts.
                            Concept.newBuilder()
                                .setId("people")  // You could search by concept Name as well.
                                .setValue(1f)  // Value of 0 will search for images that don't have the concept.
                        )
                    )
                )
            )
        )    
    )
    .build()
);

if (postAnnotationsSearchesResponse.getStatus().getCode() != StatusCode.SUCCESS) {
  throw new RuntimeException("Post annotations searches failed, status: " + postAnnotationsSearchesResponse.getStatus());
}

System.out.println("Found inputs " + postAnnotationsSearchesResponse.getHitsCount() + ":");
for (Hit hit : postAnnotationsSearchesResponse.getHitsList()) {
    System.out.printf("\tScore %.2f for annotation % of input %s\n", hit.getScore(), hit.getAnnotation().getId(), hit.getInput().getId())
}

gRPC NodeJS

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

stub.PostAnnotationsSearches(
    {
        searches: [
            {
                query: {
                    ranks: [
                        {
                            annotation: {
                                data: {
                                    concepts: [  // You can search by multiple concepts.
                                        {
                                            id: "people",  // You could search by concept Name as well.
                                            value: 1  // Value of 0 will search for images that don't have the concept
                                        }
                                    ]
                                }
                            }
                        }
                    ]
                }
            }
        ]
    },
    metadata,
    (err, response) => {
        if (err) {
            throw new Error(err);
        }

        if (response.status.code !== 10000) {
            throw new Error("Post annotations searches failed, status: " + response.status.description);
        }

        console.log("Search result:");
        for (const hit of response.hits) {
            console.log("\tScore " + hit.score + " for annotation: " + hit.annotation.id + " of input: ", hit.input.id);
        }
    }
);

gRPC Python

from clarifai_grpc.grpc.api import service_pb2, resources_pb2
from clarifai_grpc.grpc.api.status import status_code_pb2

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

post_annotations_searches_response = stub.PostAnnotationsSearches(
    service_pb2.PostAnnotationsSearchesRequest(
        searches = [
            resources_pb2.Search(
                query=resources_pb2.Query(
                    ranks=[
                        resources_pb2.