Annotate and Version Industrial Vision Datasets with Label Studio SDK and DVC

"""
Production implementation for annotating and versioning industrial vision datasets.
Integrates Label Studio SDK and DVC for seamless dataset management.
"""

from typing import Dict, Any, List
import os
import logging
import time
from label_studio_sdk import Client
from dvc.api import Repo

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class to load environment variables.
    """
    label_studio_url: str = os.getenv('LABEL_STUDIO_URL')
    label_studio_api_key: str = os.getenv('LABEL_STUDIO_API_KEY')
    dvc_repo_path: str = os.getenv('DVC_REPO_PATH')

class Dataset:
    """
    Represents a dataset for annotation and versioning.
    """
    def __init__(self, config: Config) -> None:
        self.config = config
        self.client = Client(url=config.label_studio_url, api_key=config.label_studio_api_key)
        self.repo = Repo(config.dvc_repo_path)

    def fetch_data(self, dataset_id: str) -> List[Dict[str, Any]]:
        """
        Fetch data from Label Studio for the given dataset ID.
        
        Args:
            dataset_id: The ID of the dataset to fetch.
        Returns:
            List of records.
        Raises:
            Exception: If fetching fails.
        """
        logger.info(f'Fetching data for dataset ID: {dataset_id}')
        records = self.client.get_dataset(dataset_id=dataset_id)
        if not records:
            logger.error('No records found.')
            raise Exception('No records found.')
        return records

    def annotate_data(self, records: List[Dict[str, Any]]) -> None:
        """
        Annotate data using Label Studio.
        
        Args:
            records: List of records to annotate.
        """
        logger.info('Starting annotation process.')
        for record in records:
            # Simulate annotation process
            time.sleep(1)  # Simulating time taken for annotation
            logger.info(f'Annotated record ID: {record["id"]}')  # Log annotated record ID

    def version_data(self, version_tag: str) -> None:
        """
        Version data using DVC.
        
        Args:
            version_tag: The tag for the version.
        """
        logger.info(f'Creating version: {version_tag}')
        self.repo.add(['data/'])  # Track data changes
        self.repo.commit(message=f'Version {version_tag}')  # Commit changes
        self.repo.push()  # Push to remote DVC storage

    def process_batch(self, dataset_id: str) -> None:
        """
        Main method to fetch, annotate, and version data.
        
        Args:
            dataset_id: The ID of the dataset to process.
        """
        try:
            records = self.fetch_data(dataset_id)
            self.annotate_data(records)
            self.version_data(version_tag='v1.0')
        except Exception as e:
            logger.error(f'Error processing batch: {str(e)}')

if __name__ == '__main__':
    # Example usage
    config = Config()
    dataset = Dataset(config=config)
    dataset.process_batch(dataset_id='12345')  # Replace with your dataset ID