liminm/clarifai-python-grpc

Clarifai gRPC Python client

Clarifai Python gRPC Client

This is the official Clarifai gRPC Python client for interacting with our powerful recognition API. Clarifai provides a platform for data scientists, developers, researchers and enterprises to master the entire artificial intelligence lifecycle. Gather valuable business insights from images, video and text using computer vision and natural language processing.

• Try the Clarifai demo at: https://clarifai.com/demo
• Sign up for a free account at: https://portal.clarifai.com/signup
• Read the documentation at: https://docs.clarifai.com/

Installation

pip install clarifai-grpc

Getting started

Construct the V2Stub object using which you'll access all the Clarifai API functionality:

from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
from clarifai_grpc.grpc.api import service_pb2_grpc

stub = service_pb2_grpc.V2Stub(ClarifaiChannel.get_grpc_channel())

Alternatives to the encrypted gRPC channel (ClarifaiChannel.get_grpc_channel()) are:

• the HTTPS+JSON channel (ClarifaiChannel.get_json_channel()), and
• the unencrypted gRPC channel (ClarifaiChannel.get_insecure_grpc_channel()).

We only recommend them in special cases.

Predict concepts in an image:

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(
    # This is the model ID of a publicly available General model. You may use any other public or custom model ID.
    model_id='aaa03c23b3724a16a56b629203edc62c',
    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))

See the Clarifai API documentation for all available functionality.

Troubleshooting

I get the following error when installing the library: Failed building wheel for grpcio

Try upgrading setuptools to a version 40.7.1 or higher.

pip install --upgrade setuptools

Source: grpc/grpc#17829