Update LICENSE to AGPL-3.0 (#2031)

ultralytics/datasets/Argoverse.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # Argoverse-HD dataset (ring-front-center camera) http://www.cs.cmu.edu/~mengtial/proj/streaming/ by Argo AI
 # Example usage: yolo train data=Argoverse.yaml
 # parent

ultralytics/datasets/GlobalWheat2020.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # Global Wheat 2020 dataset http://www.global-wheat.com/ by University of Saskatchewan
 # Example usage: yolo train data=GlobalWheat2020.yaml
 # parent

ultralytics/datasets/ImageNet.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # ImageNet-1k dataset https://www.image-net.org/index.php by Stanford University
 # Simplified class names from https://github.com/anishathalye/imagenet-simple-labels
 # Example usage: yolo train task=classify data=imagenet

ultralytics/datasets/Objects365.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # Objects365 dataset https://www.objects365.org/ by Megvii
 # Example usage: yolo train data=Objects365.yaml
 # parent

ultralytics/datasets/SKU-110K.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19 by Trax Retail
 # Example usage: yolo train data=SKU-110K.yaml
 # parent

ultralytics/datasets/VOC.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC by University of Oxford
 # Example usage: yolo train data=VOC.yaml
 # parent

ultralytics/datasets/VisDrone.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset by Tianjin University
 # Example usage: yolo train data=VisDrone.yaml
 # parent

ultralytics/datasets/coco-pose.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO 2017 dataset http://cocodataset.org by Microsoft
 # Example usage: yolo train data=coco-pose.yaml
 # parent

ultralytics/datasets/coco.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO 2017 dataset http://cocodataset.org by Microsoft
 # Example usage: yolo train data=coco.yaml
 # parent

ultralytics/datasets/coco128-seg.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO128-seg dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
 # Example usage: yolo train data=coco128.yaml
 # parent

ultralytics/datasets/coco128.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
 # Example usage: yolo train data=coco128.yaml
 # parent

ultralytics/datasets/coco8-pose.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO8-pose dataset (first 8 images from COCO train2017) by Ultralytics
 # Example usage: yolo train data=coco8-pose.yaml
 # parent

ultralytics/datasets/coco8-seg.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO8-seg dataset (first 8 images from COCO train2017) by Ultralytics
 # Example usage: yolo train data=coco8-seg.yaml
 # parent

ultralytics/datasets/coco8.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # COCO8 dataset (first 8 images from COCO train2017) by Ultralytics
 # Example usage: yolo train data=coco8.yaml
 # parent

ultralytics/datasets/xView.yaml

@@ -1,4 +1,4 @@
-# Ultralytics YOLO 🚀, GPL-3.0 license
+# Ultralytics YOLO 🚀, AGPL-3.0 license
 # DIUx xView 2018 Challenge https://challenge.xviewdataset.org by U.S. National Geospatial-Intelligence Agency (NGA)
 # --------  DOWNLOAD DATA MANUALLY and jar xf val_images.zip to 'datasets/xView' before running train command!  --------
 # Example usage: yolo train data=xView.yaml