added models and reports

dvc.lock

@@ -0,0 +1,25 @@
+schema: '2.0'
+stages:
+ train:
+ cmd: python src/train.py
+ deps:
+ - path: data/raw/wildfire-raw-yolov8
+ md5: ffe9083905cf64817ca61146b3356bb6.dir
+ size: 28867246
+ nfiles: 1482
+ - path: src/params.yaml
+ md5: a0c123b909925d3386149e8b024832a0
+ size: 215
+ - path: src/train.py
+ md5: d2675f1ccbf8af2b7c25485e47c4c783
+ size: 990
+ - path: src/utils.py
+ md5: e1585268f1a61213ac6e51f7abf0d47f
+ size: 1090
+ outs:
+ - path: models/model.pt
+ md5: 8198bbc4220f971f09595a135320f968
+ size: 6226104
+ - path: reports/train_metrics.csv
+ md5: fb687ccb189b9b1fe433eac7c2b4304f
+ size: 672

dvc.yaml

@@ -5,6 +5,10 @@ stages:
  - data/raw/wildfire-raw-yolov8
  - src/train.py
  - src/params.yaml
+ - src/utils.py
  outs:
- - runs/:
+ - models/model.pt:
  persist: true
+ metrics:
+ - reports/train_metrics.csv:
+ cache: false

models/.gitignore

@@ -0,0 +1 @@
+/model.pt

reports/train_metrics.csv

@@ -0,0 +1,2 @@
+ epoch, train/box_loss, train/cls_loss, train/dfl_loss, metrics/precision(B), metrics/recall(B), metrics/mAP50(B), metrics/mAP50-95(B), val/box_loss, val/cls_loss, val/dfl_loss, lr/pg0, lr/pg1, lr/pg2
+ 0, 1.9822, 4.1505, 1.6088, 0.00279, 0.83673, 0.04395, 0.0187, 2.0868, 4.2883, 1.5972, 0.070462, 0.0032821, 0.0032821

src/train.py

@@ -1,13 +1,15 @@
-from ultralytics import YOLO
-import yaml
-from pathlib import Path
 import os
+from pathlib import Path
+
+import yaml
+from ultralytics import YOLO
+
+from utils import save_metrics, save_model
 
 
 ROOT_DIR = Path(__file__).resolve().parents[1] # root directory absolute path
 DATA_DIR = os.path.join(ROOT_DIR, "data/raw/wildfire-raw-yolov8")
 DATA_YAML = os.path.join(DATA_DIR, "data.yaml")
-print(DATA_YAML)
 
 
 if __name__ == '__main__':
@@ -31,8 +33,13 @@
  name=params['name']
  )
 
- # evaluate model 
- model.val()
+ # save model
+ save_model(experiment_name=params['name']) 
+
+ # save metrics 
+ save_metrics(experiment_name=params['name'])
+
+
 
 
 

src/utils.py

@@ -0,0 +1,27 @@
+import os
+import shutil
+from pathlib import Path
+
+ROOT_DIR = Path(__file__).resolve().parents[1] # root directory absolute path
+
+
+def save_model(experiment_name: str) -> None:
+ """ saves the weights of trained model to the models directory """ 
+ if os.path.isdir('runs'):
+ model_weights = experiment_name + "/weights/best.pt"
+ path_model_weights = os.path.join(ROOT_DIR, "runs/detect", model_weights)
+
+ shutil.copy(src=path_model_weights, dst=f'{ROOT_DIR}/models/model.pt')
+
+
+def save_metrics(experiment_name: str) -> None:
+ """ saves training metrics and confusion matrix to the reports directory """ 
+ if os.path.isdir('runs'):
+ path_metrics = os.path.join(ROOT_DIR, "runs/detect", experiment_name)
+ # save experiment training metrics 
+ shutil.copy(src=f'{path_metrics}/results.csv', dst=f'{ROOT_DIR}/reports/train_metrics.csv')
+
+ # save the confusion matrix associated to the training experiment
+ shutil.copy(src=f'{path_metrics}/confusion_matrix.png', dst=f'{ROOT_DIR}/reports/train_confision_matric.png')
+
+