@sconedev/ai_toolkit/dist/models/onnxModels.js

Simplify AI integration in web apps with local and offline model support

// Collection of pre-defined models
export const predefinedModels = {
    // Text classification model (example)
    'text-classification': {
        name: 'text-classification',
        modelUrl: 'https://cdn.example.com/models/text-classification.onnx', // Replace with actual URL
        inputNames: ['input_ids', 'attention_mask', 'token_type_ids'],
        outputNames: ['output'],
        inputShapes: [[1, 128], [1, 128], [1, 128]] // Batch size 1, sequence length 128
    },
    // Image classification model (example)
    'image-classification': {
        name: 'image-classification',
        modelUrl: 'https://cdn.example.com/models/image-classification.onnx', // Replace with actual URL
        inputNames: ['input'],
        outputNames: ['output'],
        inputShapes: [[1, 3, 224, 224]] // Batch size 1, 3 channels, 224x224 resolution
    },
    // Object detection model (example)
    'object-detection': {
        name: 'object-detection',
        modelUrl: 'https://cdn.example.com/models/object-detection.onnx', // Replace with actual URL
        inputNames: ['input'],
        outputNames: ['boxes', 'scores', 'classes'],
        inputShapes: [[1, 3, 640, 640]] // Batch size 1, 3 channels, 640x640 resolution
    }
};
// Function to get model config by name
export function getModelConfig(modelName) {
    const model = predefinedModels[modelName];
    if (!model) {
        throw new Error(`Model '${modelName}' not found in predefined models`);
    }
    return model;
}
// Function to register a custom model
export function registerCustomModel(config) {
    predefinedModels[config.name] = config;
}