schema: '2.0' stages: data_ingestion: cmd: python src/kidney_classification/pipeline/stage_01_data_ingestion.py deps: - path: config/config.yaml hash: md5 md5: 23d61aa500e4da63569da56d61ddb49e size: 568 - path: src/kidney_classification/pipeline/stage_01_data_ingestion.py hash: md5 md5: 0496157b33ff2c7182935a33c605f461 size: 955 outs: - path: artifacts/data_ingestion/CT-KIDNEY-DATASET-Normal-Cyst-Tumor-Stone hash: md5 md5: 47292b3e13804acbce0f2b4ce55edc57.dir size: 887719156 nfiles: 5511 prepare_base_model: cmd: python src/kidney_classification/pipeline/stage_02_prepare_base_model.py deps: - path: config/config.yaml hash: md5 md5: 23d61aa500e4da63569da56d61ddb49e size: 568 - path: src/kidney_classification/pipeline/stage_02_prepare_base_model.py hash: md5 md5: 27f16408dee8b42a215b576052e54bb2 size: 950 params: params.yaml: CLASSES: 4 IMAGE_SIZE: - 150 - 150 - 3 INCLUDE_TOP: false WEIGHTS: imagenet outs: - path: artifacts/prepare_base_model hash: md5 md5: 2721c46e50849883acd55e5d4e3dcefb.dir size: 60010269 nfiles: 1 training: cmd: python src/kidney_classification/pipeline/stage_03_model_training.py deps: - path: artifacts/data_ingestion/CT-KIDNEY-DATASET-Normal-Cyst-Tumor-Stone hash: md5 md5: ec42dfce2ae993cf49f6d499a389c93e.dir size: 1661580918 nfiles: 12446 - path: artifacts/prepare_base_model hash: md5 md5: a4f718a24c253b4e539f7ba2dc9d3442.dir size: 59997688 nfiles: 1 - path: config/config.yaml hash: md5 md5: bc47b5f88a0220822ff7921144b69204 size: 565 - path: src/kidney_classification/pipeline/stage_03_model_training.py hash: md5 md5: cb8342c5c2f23c4d395f299924161231 size: 941 params: params.yaml: BATCH_SIZE: 32 EPOCHS: 15 IMAGE_SIZE: - 150 - 150 - 3 outs: - path: artifacts/training/model.h5 hash: md5 md5: 17969099556c165c584938f53a3fc085 size: 62136448 evaluation: cmd: python src/kidney_classification/pipeline/stage_04_model_evaluation_with_mlflow.py deps: - path: artifacts/data_ingestion/CT-KIDNEY-DATASET-Normal-Cyst-Tumor-Stone hash: md5 md5: ec42dfce2ae993cf49f6d499a389c93e.dir size: 1661580918 nfiles: 12446 - path: artifacts/training/model.h5 hash: md5 md5: 17969099556c165c584938f53a3fc085 size: 62136448 - path: config/config.yaml hash: md5 md5: bc47b5f88a0220822ff7921144b69204 size: 565 - path: src/kidney_classification/pipeline/stage_04_model_evaluation_with_mlflow.py hash: md5 md5: 7c91c2fdf529e4dcf7dec2684eb3d212 size: 892 params: params.yaml: BATCH_SIZE: 32 EPOCHS: 15 IMAGE_SIZE: - 150 - 150 - 3 outs: - path: scores.json hash: md5 md5: e80b69c44a4cf771b208a549d9e5ae30 size: 58