examples/vision-pipeline.okt

PROJECT "VisionClassifier"
DESCRIPTION "Complete computer vision pipeline with image augmentation and ONNX export"
VERSION "1.0"
AUTHOR "OktoSeek"

DATASET {
    train: "dataset/images/train/"
    validation: "dataset/images/val/"
    test: "dataset/images/test/"
    format: "image+caption"
    type: "vision"
    language: "en"
    augmentation: ["flip", "rotate", "brightness", "contrast", "crop"]
}

MODEL {
    base: "oktoseek/vision-base"
    architecture: "vision-transformer"
    parameters: 86M
    context_window: 224
    precision: "fp16"
}

TRAIN {
    epochs: 50
    batch_size: 32
    learning_rate: 0.001
    optimizer: "adam"
    scheduler: "cosine"
    loss: "cross_entropy"
    device: "cuda"
    gpu: true
    mixed_precision: true
    early_stopping: true
    checkpoint_steps: 500
    checkpoint_path: "./checkpoints/vision"
    weight_decay: 0.0001
    gradient_clip: 1.0
    warmup_steps: 1000
    save_strategy: "steps"
}

METRICS {
    accuracy
    precision
    recall
    f1
    f1_macro
    f1_micro
    confusion_matrix
}

VALIDATE {
    on_train: true
    on_validation: true
    frequency: 1
    save_best_model: true
    metric_to_monitor: "accuracy"
}

EXPORT {
    format: ["onnx", "okm", "tflite"]
    path: "export/"
    quantization: "int8"
    optimize_for: "speed"
}

DEPLOY {
    target: "web"
    endpoint: "https://api.example.com/vision"
    requires_auth: true
    max_concurrent_requests: 100
}

SECURITY {
    encrypt_model: true
    watermark: true
}

LOGGING {
    save_logs: true
    metrics_file: "runs/vision-classifier/metrics.json"
    training_file: "runs/vision-classifier/training_logs.json"
    log_level: "info"
    log_every: 50
}