minor changes

requirements.txt

@@ -1,3 +1,6 @@
 dvc==2.51.0
 ultralytics==8.0.58
+python-dotenv==1.0.0
+mlflow==2.2.2
+
 

src/train.py

@@ -54,13 +54,12 @@
 
  # save model
  model_path = save_model(experiment_name=params['name']) 
- # log model path with mlflow 
+ # log model artifact to mlflow 
  mlflow.log_artifact(model_path)
 
  # save metrics csv file and training params 
  save_metrics_and_params(experiment_name=params['name'])
- # convert metrics from csv to json
- convert_metrics_csv_to_json(metrics_path, params['name'])
+
 
 
 

src/utils.py

@@ -1,8 +1,7 @@
 import os
 import shutil
 from pathlib import Path
-import pandas as pd
-import json
+
 
 ROOT_DIR = Path(__file__).resolve().parents[1] # root directory absolute path
 
@@ -13,20 +12,7 @@ def save_model(experiment_name: str):
  model_weights = experiment_name + "/weights/best.pt"
  path_model_weights = os.path.join(ROOT_DIR, "runs/detect", model_weights)
 
- return shutil.copy(src=path_model_weights, dst=f'{ROOT_DIR}/models/model.pt')
-
-
-def csv_to_json(csv_file_path:str, dest_file_path: str):
- df = pd.read_csv(csv_file_path)
- df.to_json(dest_file_path, orient="index")
-
-
-def convert_metrics_csv_to_json(dest_file_path: str, experiment_name:str):
- # convert metrics from csv to json format in order to track the with DVC
- if os.path.isdir('runs'):
- path_metrics = os.path.join(ROOT_DIR, "runs/detect", experiment_name)
- path_metrics = os.path.join(path_metrics, 'results.csv')
- csv_to_json(path_metrics, dest_file_path)
+ shutil.copy(src=path_model_weights, dst=f'{ROOT_DIR}/models/model.pt')
 
 
 def save_metrics_and_params(experiment_name: str) -> None:
@@ -43,5 +29,3 @@ def save_metrics_and_params(experiment_name: str) -> None:
  # save training params
  shutil.copy(src=f'{path_metrics}/args.yaml', dst=f'{ROOT_DIR}/reports/train_params.yaml')
 
-
-save_model('yolov8s_exp_v0')