Clarifai Rust gRPC Client

This is the official Clarifai gRPC Rust client for interacting with our powerful recognition API. The Clarifai API offers image and video recognition as a service. Whether you have one image or billions, you are only steps away from using artificial intelligence to recognize your visual content.

• 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

WIP

Getting started

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

```rust use grpcio::{CallOption, MetadataBuilder}; use protobuf::{RepeatedField};

use crate::grpc::resources::{Data, Image, Input}; use crate::grpc::service::PostModelOutputsRequest; use crate::grpc::servicegrpc::V2Client; use crate::grpc::statuscode::StatusCode;

use clarifaigrpc::clarifaichannel;

let client = V2Client::new(clarifai_channel::grpc());

// Setup authentication. let auth = "Key YOURCLARIFAIAPIKEYORPAT".tostring();

let mut builder = MetadataBuilder::withcapacity(1); builder.addstr("Authorization", &auth).unwrap(); let metadata = builder.build(); let call_opt = CallOption::default().headers(metadata); ```

Predict concepts in an image:

```rust let request = PostModelOutputsRequest { modelid: GENERALMODELID.tostring(), inputs: RepeatedField::from(vec![Input { data: SingularPtrField::some(Data { image: SingularPtrField::some(Image { url: "https://samples.clarifai.com/dog2.jpeg".tostring(), ..Default::default() }), ..Default::default() }), ..Default::default() }]), ..Default::default() }; let response = client .postmodeloutputsopt(&request, call_opt) .expect("Failure");

let status = response.getstatus(); if status.getcode() != StatusCode::SUCCESS { println!("Failure response:"); println!("\t{}", status.getcode().value()); println!("\t{}", status.getdescription()); println!("\t{}", status.get_details()); exit(1); }

println!("Predicted concepts:"); for concept in response.getoutputs()[0].getdata().getconcepts() { println!("\t{}: {}", concept.getname(), concept.get_value()); } ```