The Celebrity Model is makes it easy to sort and label images that contain the world's most famous people.  

For example, the Celebrity Model might return the following information for the image above:

Getting Started

First things first. You will need to set up a Clarifai account and create an application. This how-to article shows you how to label food items with the Clarifai API and through Portal. If you would like to identify celebrities items via API, you will also need to generate an API key.

Identify celebrities in Portal 

You can do almost anything that Clarifai can do with Clarifai Portal, and we work hard to make Portal the world's easiest interface for using AI. To identify celebrities in portal, upload your images and create a new "celebrity" workflow. 

Create your application and choose "General" as your base workflow

To use the celebrity model, we will first create an app that uses "General" as the base workflow. 

Navigate to Model Mode and create a new workflow

Next, we will want to create a new workflow that uses the celebrity model. Just navigate to Model Mode on the right hand sidebar and click "Create New Workflow" in the upper righthand corner of the screen. 

Add the celebrity "visual classifier" to your workflow

Now we will add just one model to the work flow: the celebrity "visual classifier". Be sure to select "clarifai" as the user in the lefthand dropdown menu. You can then filter your results by model type. Select "visual classifier". Click "ADD" to add the model to your workflow, and then click "CREATE WORKFLOW"

Select your new "celebrity" workflow as the app workflow

Now navigate to view your image in Explorer. In the righthand sidebar you can click the "APP WORKFLOW" tab, and click the gear icon. Finally select your new workflow, and view your predictions. 

Identify celebrities in a local image

Use the following Python snippet as an example of how to run a prediction on an image hosted on your local computer. For more details and information on working with predictions in our other client languages, please refer to our API documentation.

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

# This is how you authenticate.
metadata = (('authorization', 'Key {{YOUR_CLARIFAI_API_KEY}}'),)

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

request = service_pb2.PostModelOutputsRequest(
    model_id='cfbb105cb8f54907bb8d553d68d9fe20',
    inputs=[
        resources_pb2.Input(
            data=resources_pb2.Data(
                image=resources_pb2.Image(
                    base64=file_bytes
                )
            )
        )      
    ])
response = stub.PostModelOutputs(request, metadata=metadata)

if response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Request failed, status code: " + str(response.status.code))

for concept in response.outputs[0].data.concepts:
    print('%12s: %.2f' % (concept.name, concept.value))

Identify celebrities in images hosted on the web

Here is an example of how to run a prediction on an image that is hosted on a URL. This snippet is in Python, but we offer support for many other client languages. Please refer to our API documentation for additional information. 

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

# This is how you authenticate.
metadata = (('authorization', 'Key {{YOUR_CLARIFAI_API_KEY}}'),)

request = service_pb2.PostModelOutputsRequest(
    model_id='cfbb105cb8f54907bb8d553d68d9fe20',
    inputs=[
      resources_pb2.Input(data=resources_pb2.Data(image=resources_pb2.Image(url='{{YOUR_IMAGE_URL}}')))
    ])
response = stub.PostModelOutputs(request, metadata=metadata)

if response.status.code != status_code_pb2.SUCCESS:
    raise Exception("Request failed, status code: " + str(response.status.code))

for concept in response.outputs[0].data.concepts:
    print('%12s: %.2f' % (concept.name, concept.value))