Standardize license headers in TOML/YAML files (#13491)

Refactor code for speed and clarity

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

data/hyps/hyp.Objects365.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hyperparameters for Objects365 training
 # python train.py --weights yolov5m.pt --data Objects365.yaml --evolve
 # See Hyperparameter Evolution tutorial for details https://github.com/ultralytics/yolov5#tutorials

data/hyps/hyp.VOC.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hyperparameters for VOC training
 # python train.py --batch 128 --weights yolov5m6.pt --data VOC.yaml --epochs 50 --img 512 --hyp hyp.scratch-med.yaml --evolve
 # See Hyperparameter Evolution tutorial for details https://github.com/ultralytics/yolov5#tutorials

data/hyps/hyp.no-augmentation.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hyperparameters when using Albumentations frameworks
 # python train.py --hyp hyp.no-augmentation.yaml
 # See https://github.com/ultralytics/yolov5/pull/3882 for YOLOv5 + Albumentations Usage examples

data/hyps/hyp.scratch-high.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hyperparameters for high-augmentation COCO training from scratch
 # python train.py --batch 32 --cfg yolov5m6.yaml --weights '' --data coco.yaml --img 1280 --epochs 300
 # See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials

data/hyps/hyp.scratch-low.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hyperparameters for low-augmentation COCO training from scratch
 # python train.py --batch 64 --cfg yolov5n6.yaml --weights '' --data coco.yaml --img 640 --epochs 300 --linear
 # See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials

data/hyps/hyp.scratch-med.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLOv5 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hyperparameters for medium-augmentation COCO training from scratch
 # python train.py --batch 32 --cfg yolov5m6.yaml --weights '' --data coco.yaml --img 1280 --epochs 300
 # See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials