Hub Usage Guide

#include <xinfer/hub/downloader.h>
 
std::string download_engine(
    const std::string& model_id,
    const HardwareTarget& target,
    const std::string& cache_dir = "./xinfer_cache",
    const std::string& hub_url = "https://api.your-ignition-hub.com"
);

#include <xinfer/hub/downloader.h>
#include <xinfer/core/engine.h>
#include <iostream>
 
int main() {
    try {
        // 1. Specify the exact engine we need.
        std::string model_id = "resnet50-imagenet";
        xinfer::hub::HardwareTarget my_gpu_target = {
            .gpu_architecture = "RTX_4090",       // Or "sm_89"
            .tensorrt_version = "10.1.0",
            .precision = "FP16"
        };
 
        // 2. Download the engine file. This will be fast if it's already cached.
        std::cout << "Downloading engine...\n";
        std::string engine_path = xinfer::hub::download_engine(model_id, my_gpu_target);
        
        // 3. Now, use the downloaded engine with the core::InferenceEngine.
        std::cout << "Loading engine: " << engine_path << "\n";
        xinfer::core::InferenceEngine engine(engine_path);
        
        std::cout << "Engine loaded successfully!\n";
        // ... proceed with your custom inference pipeline ...
 
    } catch (const std::exception& e) {
        std::cerr << "Error: " << e.what() << std::endl;
        return 1;
    }
    return 0;
}

#include <xinfer/zoo/vision/classifier.h>
#include <xinfer/hub/model_info.h> // The HardwareTarget struct is defined here
#include <opencv2/opencv.hpp>
#include <iostream>
 
int main() {
    try {
        // 1. Define the model we want from the hub and our current hardware.
        std::string model_id = "resnet50-imagenet";
        xinfer::hub::HardwareTarget my_gpu_target;
        my_gpu_target.gpu_architecture = "RTX_4090";
        my_gpu_target.tensorrt_version = "10.1.0";
        my_gpu_target.precision = "FP16";
        
        // 2. Instantiate the classifier with the model_id and target.
        //    This single constructor call does everything:
        //    - Downloads the correct .engine file from the Ignition Hub.
        //    - Downloads the associated labels.txt file.
        //    - Loads the engine and initializes the pre-processor.
        std::cout << "Initializing classifier from Ignition Hub...\n";
        xinfer::zoo::vision::ImageClassifier classifier(model_id, my_gpu_target);
        std::cout << "Classifier ready!\n";
 
        // 3. The classifier is now ready for immediate, high-performance inference.
        cv::Mat image = cv::imread("my_image.jpg");
        auto results = classifier.predict(image);
 
        // ... print results ...
 
    } catch (const std::exception& e) {
        std::cerr << "An error occurred: " << e.what() << std::endl;
        return 1;
    }
    return 0;
}