Improve headers and comments in TOML/YAML files (#18698)

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

ultralytics/cfg/datasets/Argoverse.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Argoverse-HD dataset (ring-front-center camera) https://www.cs.cmu.edu/~mengtial/proj/streaming/ by Argo AI
 # Documentation: https://docs.ultralytics.com/datasets/detect/argoverse/
 # Example usage: yolo train data=Argoverse.yaml

ultralytics/cfg/datasets/DOTAv1.5.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # DOTA 1.5 dataset https://captain-whu.github.io/DOTA/index.html for object detection in aerial images by Wuhan University
 # Documentation: https://docs.ultralytics.com/datasets/obb/dota-v2/
 # Example usage: yolo train model=yolov8n-obb.pt data=DOTAv1.5.yaml

ultralytics/cfg/datasets/DOTAv1.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # DOTA 1.0 dataset https://captain-whu.github.io/DOTA/index.html for object detection in aerial images by Wuhan University
 # Documentation: https://docs.ultralytics.com/datasets/obb/dota-v2/
 # Example usage: yolo train model=yolov8n-obb.pt data=DOTAv1.yaml

ultralytics/cfg/datasets/GlobalWheat2020.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Global Wheat 2020 dataset https://www.global-wheat.com/ by University of Saskatchewan
 # Documentation: https://docs.ultralytics.com/datasets/detect/globalwheat2020/
 # Example usage: yolo train data=GlobalWheat2020.yaml

ultralytics/cfg/datasets/ImageNet.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/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
 # Documentation: https://docs.ultralytics.com/datasets/classify/imagenet/

ultralytics/cfg/datasets/Objects365.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Objects365 dataset https://www.objects365.org/ by Megvii
 # Documentation: https://docs.ultralytics.com/datasets/detect/objects365/
 # Example usage: yolo train data=Objects365.yaml

ultralytics/cfg/datasets/SKU-110K.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19 by Trax Retail
 # Documentation: https://docs.ultralytics.com/datasets/detect/sku-110k/
 # Example usage: yolo train data=SKU-110K.yaml

ultralytics/cfg/datasets/VOC.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC by University of Oxford
 # Documentation: # Documentation: https://docs.ultralytics.com/datasets/detect/voc/
 # Example usage: yolo train data=VOC.yaml

ultralytics/cfg/datasets/VisDrone.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset by Tianjin University
 # Documentation: https://docs.ultralytics.com/datasets/detect/visdrone/
 # Example usage: yolo train data=VisDrone.yaml

ultralytics/cfg/datasets/african-wildlife.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # African-wildlife dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/detect/african-wildlife/
 # Example usage: yolo train data=african-wildlife.yaml

ultralytics/cfg/datasets/brain-tumor.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Brain-tumor dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/detect/brain-tumor/
 # Example usage: yolo train data=brain-tumor.yaml

ultralytics/cfg/datasets/carparts-seg.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Carparts-seg dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/segment/carparts-seg/
 # Example usage: yolo train data=carparts-seg.yaml

ultralytics/cfg/datasets/coco-pose.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO 2017 Keypoints dataset https://cocodataset.org by Microsoft
 # Documentation: https://docs.ultralytics.com/datasets/pose/coco/
 # Example usage: yolo train data=coco-pose.yaml

ultralytics/cfg/datasets/coco.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO 2017 dataset https://cocodataset.org by Microsoft
 # Documentation: https://docs.ultralytics.com/datasets/detect/coco/
 # Example usage: yolo train data=coco.yaml

ultralytics/cfg/datasets/coco128-seg.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO128-seg dataset https://www.kaggle.com/datasets/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/segment/coco/
 # Example usage: yolo train data=coco128.yaml

ultralytics/cfg/datasets/coco128.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO128 dataset https://www.kaggle.com/datasets/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/detect/coco/
 # Example usage: yolo train data=coco128.yaml

ultralytics/cfg/datasets/coco8-pose.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO8-pose dataset (first 8 images from COCO train2017) by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/pose/coco8-pose/
 # Example usage: yolo train data=coco8-pose.yaml

ultralytics/cfg/datasets/coco8-seg.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO8-seg dataset (first 8 images from COCO train2017) by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/segment/coco8-seg/
 # Example usage: yolo train data=coco8-seg.yaml

ultralytics/cfg/datasets/coco8.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # COCO8 dataset (first 8 images from COCO train2017) by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/detect/coco8/
 # Example usage: yolo train data=coco8.yaml

ultralytics/cfg/datasets/crack-seg.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Crack-seg dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/segment/crack-seg/
 # Example usage: yolo train data=crack-seg.yaml

ultralytics/cfg/datasets/dog-pose.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Dogs dataset http://vision.stanford.edu/aditya86/ImageNetDogs/ by Stanford
 # Documentation: https://docs.ultralytics.com/datasets/pose/dog-pose/
 # Example usage: yolo train data=dog-pose.yaml

ultralytics/cfg/datasets/dota8.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # DOTA8 dataset 8 images from split DOTAv1 dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/obb/dota8/
 # Example usage: yolo train model=yolov8n-obb.pt data=dota8.yaml

ultralytics/cfg/datasets/hand-keypoints.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Hand Keypoints dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/pose/hand-keypoints/
 # Example usage: yolo train data=hand-keypoints.yaml

ultralytics/cfg/datasets/lvis.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # LVIS dataset http://www.lvisdataset.org by Facebook AI Research.
 # Documentation: https://docs.ultralytics.com/datasets/detect/lvis/
 # Example usage: yolo train data=lvis.yaml

ultralytics/cfg/datasets/medical-pills.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Medical-pills dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/detect/medical-pills/
 # Example usage: yolo train data=medical-pills.yaml

ultralytics/cfg/datasets/open-images-v7.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Open Images v7 dataset https://storage.googleapis.com/openimages/web/index.html by Google
 # Documentation: https://docs.ultralytics.com/datasets/detect/open-images-v7/
 # Example usage: yolo train data=open-images-v7.yaml

ultralytics/cfg/datasets/package-seg.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Package-seg dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/segment/package-seg/
 # Example usage: yolo train data=package-seg.yaml

ultralytics/cfg/datasets/signature.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Signature dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/detect/signature/
 # Example usage: yolo train data=signature.yaml

ultralytics/cfg/datasets/tiger-pose.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
 # Tiger Pose dataset by Ultralytics
 # Documentation: https://docs.ultralytics.com/datasets/pose/tiger-pose/
 # Example usage: yolo train data=tiger-pose.yaml

ultralytics/cfg/datasets/xView.yaml

@@ -1,4 +1,5 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/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!  --------
 # Documentation: https://docs.ultralytics.com/datasets/detect/xview/

ultralytics/cfg/default.yaml

@@ -1,5 +1,7 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# Default training settings and hyperparameters for medium-augmentation COCO training
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Global configuration YAML with settings and hyperparameters for YOLO training, validation, prediction and export
+# For documentation see https://docs.ultralytics.com/usage/cfg/
 
 task: detect # (str) YOLO task, i.e. detect, segment, classify, pose, obb
 mode: train # (str) YOLO mode, i.e. train, val, predict, export, track, benchmark

ultralytics/cfg/models/11/yolo11-cls-resnet18.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLO11-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLO11-cls image classification model with ResNet18 backbone
+# Model docs: https://docs.ultralytics.com/models/yolo11
+# Task docs: https://docs.ultralytics.com/tasks/classify
 
 # Parameters
 nc: 10 # number of classes
@@ -11,7 +14,7 @@ scales: # model compound scaling constants, i.e. 'model=yolo11n-cls.yaml' will c
   l: [1.00, 1.00, 1024]
   x: [1.00, 1.25, 1024]
 
-# YOLO11n backbone
+# ResNet18 backbone
 backbone:
   # [from, repeats, module, args]
   - [-1, 1, TorchVision, [512, "resnet18", "DEFAULT", True, 2]] # truncate two layers from the end

ultralytics/cfg/models/11/yolo11-cls.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLO11-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLO11-cls image classification model
+# Model docs: https://docs.ultralytics.com/models/yolo11
+# Task docs: https://docs.ultralytics.com/tasks/classify
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/11/yolo11-obb.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLO11 Oriented Bounding Boxes (OBB) model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/obb
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLO11-obb Oriented Bounding Boxes (OBB) model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolo11
+# Task docs: https://docs.ultralytics.com/tasks/obb
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/11/yolo11-pose.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLO11-pose keypoints/pose estimation model. For Usage examples see https://docs.ultralytics.com/tasks/pose
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLO11-pose keypoints/pose estimation model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolo11
+# Task docs: https://docs.ultralytics.com/tasks/pose
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/11/yolo11-seg.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLO11-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/tasks/segment
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLO11-seg instance segmentation model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolo11
+# Task docs: https://docs.ultralytics.com/tasks/segment
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/11/yolo11.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLO11 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLO11 object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolo11
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/rt-detr/rtdetr-l.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# RT-DETR-l object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/models/rtdetr
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics RT-DETR-l hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/rtdetr
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/rt-detr/rtdetr-resnet101.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# RT-DETR-ResNet101 object detection model with P3-P5 outputs.
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics RT-DETR-ResNet101 hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/rtdetr
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/rt-detr/rtdetr-resnet50.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# RT-DETR-ResNet50 object detection model with P3-P5 outputs.
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics RT-DETR-ResNet50 hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/rtdetr
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/rt-detr/rtdetr-x.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# RT-DETR-x object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/models/rtdetr
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics RT-DETR-x hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/rtdetr
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v10/yolov10b.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv10b object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov10
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v10/yolov10l.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv10l object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov10
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v10/yolov10m.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv10m object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov10
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v10/yolov10n.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv10n object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov10
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v10/yolov10s.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv10s object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov10
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v10/yolov10x.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv10 object detection model. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv10x object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov10
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v3/yolov3-spp.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv3-SPP object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/models/yolov3
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv3-SPP object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov3
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v3/yolov3-tiny.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv3-tiny object detection model with P4-P5 outputs. For details see https://docs.ultralytics.com/models/yolov3
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv3-tiiny object detection model with P4/16 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov3
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v3/yolov3.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv3 object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/models/yolov3
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv3 object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov3
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v5/yolov5-p6.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv5 object detection model with P3-P6 outputs. For details see https://docs.ultralytics.com/models/yolov5
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv5 object detection model with P3/8 - P6/64 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov5
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v5/yolov5.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv5 object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/models/yolov5
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv5 object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov5
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v6/yolov6.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv6 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/models/yolov6
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Meituan YOLOv6 object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov6
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-cls-resnet101.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-cls image classification model with ResNet101 backbone
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/classify
 
 # Parameters
 nc: 1000 # number of classes

ultralytics/cfg/models/v8/yolov8-cls-resnet50.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-cls image classification model with ResNet50 backbone
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/classify
 
 # Parameters
 nc: 1000 # number of classes

ultralytics/cfg/models/v8/yolov8-cls.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-cls image classification model with YOLO backbone
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/classify
 
 # Parameters
 nc: 1000 # number of classes

ultralytics/cfg/models/v8/yolov8-ghost-p2.yaml

@@ -1,5 +1,9 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8 object detection model with P2/4 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/detect
+# Employs Ghost convolutions and modules proposed in Huawei's GhostNet in https://arxiv.org/abs/1911.11907v2
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-ghost-p6.yaml

@@ -1,5 +1,9 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8 object detection model with P3/8 - P6/64 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/detect
+# Employs Ghost convolutions and modules proposed in Huawei's GhostNet in https://arxiv.org/abs/1911.11907v2
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-ghost.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8 object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/detect
 # Employs Ghost convolutions and modules proposed in Huawei's GhostNet in https://arxiv.org/abs/1911.11907v2
 
 # Parameters

ultralytics/cfg/models/v8/yolov8-obb.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 Oriented Bounding Boxes (OBB) model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-obb Oriented Bounding Boxes (OBB) model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/obb
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-p2.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8 object detection model with P2/4 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-p6.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8 object detection model with P3/8 - P6/64 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-pose-p6.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-pose-p6 keypoints/pose estimation model. For Usage examples see https://docs.ultralytics.com/tasks/pose
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-pose keypoints/pose estimation model with P3/8 - P6/64 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/pose
 
 # Parameters
 nc: 1 # number of classes

ultralytics/cfg/models/v8/yolov8-pose.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-pose keypoints/pose estimation model. For Usage examples see https://docs.ultralytics.com/tasks/pose
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-pose keypoints/pose estimation model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/pose
 
 # Parameters
 nc: 1 # number of classes

ultralytics/cfg/models/v8/yolov8-rtdetr.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-RTDETR hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/rtdetr
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-seg-p6.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-seg-p6 instance segmentation model. For Usage examples see https://docs.ultralytics.com/tasks/segment
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-seg instance segmentation model with P3/8 - P6/64 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/segment
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-seg.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/tasks/segment
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-seg instance segmentation model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/segment
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-world.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-World object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-World hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolo-world
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8-worldv2.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8-World-v2 object detection model with P3-P5 outputs. For details see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8-Worldv2 hybrid object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolo-world
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v8/yolov8.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Ultralytics YOLOv8 object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov8
+# Task docs: https://docs.ultralytics.com/tasks/detect
 
 # Parameters
 nc: 80 # number of classes

ultralytics/cfg/models/v9/yolov9c-seg.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9c-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9c-seg instance segmentation model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/segment
 # 654 layers, 27897120 parameters, 159.4 GFLOPs
 
 # Parameters

ultralytics/cfg/models/v9/yolov9c.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9c object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9c object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/detect
 # 618 layers, 25590912 parameters, 104.0 GFLOPs
 
 # Parameters

ultralytics/cfg/models/v9/yolov9e-seg.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9e-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9e-seg instance segmentation model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/segment
 # 1261 layers, 60512800 parameters, 248.4 GFLOPs
 
 # Parameters

ultralytics/cfg/models/v9/yolov9e.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9e object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9e object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/detect
 # 1225 layers, 58206592 parameters, 193.0 GFLOPs
 
 # Parameters

ultralytics/cfg/models/v9/yolov9m.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9m object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9m object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/detect
 # 603 layers, 20216160 parameters, 77.9 GFLOPs
 
 # Parameters

ultralytics/cfg/models/v9/yolov9s.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9s object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9s object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/detect
 # 917 layers, 7318368 parameters, 27.6 GFLOPs
 
 # Parameters

ultralytics/cfg/models/v9/yolov9t.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# YOLOv9t object detection model. For Usage examples see https://docs.ultralytics.com/models/yolov9
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# YOLOv9t object detection model with P3/8 - P5/32 outputs
+# Model docs: https://docs.ultralytics.com/models/yolov9
+# Task docs: https://docs.ultralytics.com/tasks/detect
 # 917 layers, 2128720 parameters, 8.5 GFLOPs
 
 # Parameters

ultralytics/cfg/solutions/default.yaml

@@ -1,5 +1,7 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# Configuration for Ultralytics Solutions: https://docs.ultralytics.com/solutions/
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Global configuration YAML with settings and arguments for Ultralytics Solutions
+# For documentation see https://docs.ultralytics.com/solutions/
 
 # Object counting settings  --------------------------------------------------------------------------------------------
 region: # list[tuple[int, int]] object counting, queue or speed estimation region points.

ultralytics/cfg/trackers/botsort.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# Default YOLO tracker settings for BoT-SORT tracker https://github.com/NirAharon/BoT-SORT
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Default Ultralytics settings for BoT-SORT tracker when using mode="track"
+# For documentation and examples see https://docs.ultralytics.com/modes/track/
+# For BoT-SORT source code see https://github.com/NirAharon/BoT-SORT
 
 tracker_type: botsort # tracker type, ['botsort', 'bytetrack']
 track_high_thresh: 0.25 # threshold for the first association

ultralytics/cfg/trackers/bytetrack.yaml

@@ -1,5 +1,8 @@
-# Ultralytics YOLO 🚀, AGPL-3.0 license
-# Default YOLO tracker settings for ByteTrack tracker https://github.com/ifzhang/ByteTrack
+# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+# Default Ultralytics settings for ByteTrack tracker when using mode="track"
+# For documentation and examples see https://docs.ultralytics.com/modes/track/
+# For ByteTrack source code see https://github.com/ifzhang/ByteTrack
 
 tracker_type: bytetrack # tracker type, ['botsort', 'bytetrack']
 track_high_thresh: 0.25 # threshold for the first association