fix augmentation - correct bboxes to be within borders+margin

Add classes = 80 as default number in yaml file

train.py

@@ -18,6 +18,8 @@ train_set = 70
 valid_set = 20
 test_set = 10
 
+DEFAULT_CLASS_NUM = 80
+
 
 def form_dataset(from_date: datetime):
     makedirs(today_dataset, exist_ok=True)
@@ -89,7 +91,10 @@ def create_yaml():
     lines = ['names:']
     for c in annotation_classes:
         lines.append(f'- {annotation_classes[c].name}')
-    lines.append(f'nc: {len(annotation_classes)}')
+    classes_count = len(annotation_classes)
+    for c in range(DEFAULT_CLASS_NUM - classes_count):
+        lines.append(f'- Class-{c + classes_count + 1}')
+    lines.append(f'nc: {DEFAULT_CLASS_NUM}')
 
     lines.append(f'test: test/images')
     lines.append(f'train: train/images')
@@ -132,17 +137,19 @@ def get_latest_model():
 
 if __name__ == '__main__':
     latest_date, latest_model = get_latest_model()
+    # create_yaml()
     # form_dataset(latest_date)
 
+
     model_name = latest_model if latest_model is not None and path.isfile(latest_model) else 'yolov8m.yaml'
     print(f'Initial model: {model_name}')
     model = YOLO(model_name)
     
-    # cur_folder = path.join(datasets_dir, f'{prefix}2024-06-18')
+    cur_folder = path.join(datasets_dir, f'{prefix}2024-09-19')
 
-    cur_folder = today_dataset
+    # cur_folder = today_dataset
     yaml = abspath(path.join(cur_folder, 'data.yaml'))
-    results = model.train(data=yaml, epochs=100, batch=60, imgsz=640)
+    results = model.train(data=yaml, epochs=100, batch=58, imgsz=640)
 
     shutil.copytree(results.save_dir, path.join(models_dir, today_folder))
     shutil.rmtree('runs')