main.py

from dotenv import load_dotenv
from cnnClassifier.pipeline.stage_01_data_ingestion import DataIngestionPipeline
from cnnClassifier.pipeline.stage_02_prepare_base_model import PrepareBaseModelPipeline
from cnnClassifier.pipeline.stage_03_model_training import ModelTrainingPipeline
from cnnClassifier import logger
from cnnClassifier.pipeline.stage_04_model_evaluation import ModelEvaluationPipeline

load_dotenv()

STAGE_NAME = "Data Ingestion Stage"

try:
    logger.info(f">>>>> stage {STAGE_NAME} started <<<<<")
    obj = DataIngestionPipeline()
    obj.main()
    logger.info(f">>>>> stage {STAGE_NAME} completed <<<<<")
except Exception as e:
    logger.exception(e)
    raise e

STAGE_NAME = "Prepare Base Model"

try:
    logger.info(f">>>>> stage {STAGE_NAME} started <<<<<")
    obj = PrepareBaseModelPipeline()
    obj.main()
    logger.info(f">>>>> stage {STAGE_NAME} completed <<<<<")
except Exception as e:
    logger.exception(e)
    raise e

STAGE_NAME = "Model Training"

try:
    logger.info(f">>>>> stage {STAGE_NAME} started <<<<<")
    obj = ModelTrainingPipeline()
    obj.main()
    logger.info(f">>>>> stage {STAGE_NAME} completed <<<<<")
except Exception as e:
    logger.exception(e)
    raise e

STAGE_NAME = "Model Evaluation and MLFlow"

try:
    logger.info(f">>>>> stage {STAGE_NAME} started <<<<<")
    obj = ModelEvaluationPipeline()
    obj.main()
    logger.info(f">>>>> stage {STAGE_NAME} completed <<<<<")
except Exception as e:
    logger.exception(e)
    raise e