Docstrings arguments cleanup (#3229)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/build_reference.py

@@ -43,8 +43,8 @@ def create_markdown(py_filepath, module_path, classes, functions):
                 header_content = f"{header_parts[0]}---{header_parts[1]}---\n\n"
 
     module_path = module_path.replace('.__init__', '')
-    md_content = [f"# {class_name}\n---\n:::{module_path}.{class_name}\n<br><br>\n" for class_name in classes]
-    md_content.extend(f"# {func_name}\n---\n:::{module_path}.{func_name}\n<br><br>\n" for func_name in functions)
+    md_content = [f"## {class_name}\n---\n### ::: {module_path}.{class_name}\n<br><br>\n" for class_name in classes]
+    md_content.extend(f"## {func_name}\n---\n### ::: {module_path}.{func_name}\n<br><br>\n" for func_name in functions)
     md_content = header_content + "\n".join(md_content)
 
     os.makedirs(os.path.dirname(md_filepath), exist_ok=True)

docs/reference/hub/__init__.md

@@ -3,42 +3,42 @@ description: Access Ultralytics HUB, manage API keys, train models, and export i
 keywords: Ultralytics, YOLO, Docs HUB, API, login, logout, reset model, export model, check dataset, HUBDatasetStats, YOLO training, YOLO model
 ---
 
-# login
+## login
 ---
-:::ultralytics.hub.login
+### ::: ultralytics.hub.login
 <br><br>
 
-# logout
+## logout
 ---
-:::ultralytics.hub.logout
+### ::: ultralytics.hub.logout
 <br><br>
 
-# start
+## start
 ---
-:::ultralytics.hub.start
+### ::: ultralytics.hub.start
 <br><br>
 
-# reset_model
+## reset_model
 ---
-:::ultralytics.hub.reset_model
+### ::: ultralytics.hub.reset_model
 <br><br>
 
-# export_fmts_hub
+## export_fmts_hub
 ---
-:::ultralytics.hub.export_fmts_hub
+### ::: ultralytics.hub.export_fmts_hub
 <br><br>
 
-# export_model
+## export_model
 ---
-:::ultralytics.hub.export_model
+### ::: ultralytics.hub.export_model
 <br><br>
 
-# get_export
+## get_export
 ---
-:::ultralytics.hub.get_export
+### ::: ultralytics.hub.get_export
 <br><br>
 
-# check_dataset
+## check_dataset
 ---
-:::ultralytics.hub.check_dataset
+### ::: ultralytics.hub.check_dataset
 <br><br>

docs/reference/hub/auth.md

@@ -3,7 +3,7 @@ description: Learn how to use Ultralytics hub authentication in your projects wi
 keywords: Ultralytics, ultralytics hub, api keys, authentication, collab accounts, requests, hub management, monitoring
 ---
 
-# Auth
+## Auth
 ---
-:::ultralytics.hub.auth.Auth
+### ::: ultralytics.hub.auth.Auth
 <br><br>

docs/reference/hub/session.md

@@ -3,7 +3,7 @@ description: Accelerate your AI development with the Ultralytics HUB Training Se
 keywords: YOLOv5, object detection, HUBTrainingSession, custom models, Ultralytics Docs
 ---
 
-# HUBTrainingSession
+## HUBTrainingSession
 ---
-:::ultralytics.hub.session.HUBTrainingSession
+### ::: ultralytics.hub.session.HUBTrainingSession
 <br><br>

docs/reference/hub/utils.md

@@ -3,22 +3,22 @@ description: Explore Ultralytics events, including 'request_with_credentials' an
 keywords: Ultralytics, Hub Utils, API Documentation, Python, requests_with_progress, Events, classes, usage, examples
 ---
 
-# Events
+## Events
 ---
-:::ultralytics.hub.utils.Events
+### ::: ultralytics.hub.utils.Events
 <br><br>
 
-# request_with_credentials
+## request_with_credentials
 ---
-:::ultralytics.hub.utils.request_with_credentials
+### ::: ultralytics.hub.utils.request_with_credentials
 <br><br>
 
-# requests_with_progress
+## requests_with_progress
 ---
-:::ultralytics.hub.utils.requests_with_progress
+### ::: ultralytics.hub.utils.requests_with_progress
 <br><br>
 
-# smart_request
+## smart_request
 ---
-:::ultralytics.hub.utils.smart_request
+### ::: ultralytics.hub.utils.smart_request
 <br><br>

docs/reference/nn/autobackend.md

@@ -3,12 +3,12 @@ description: Ensure class names match filenames for easy imports. Use AutoBacken
 keywords: AutoBackend, ultralytics, nn, autobackend, check class names, neural network
 ---
 
-# AutoBackend
+## AutoBackend
 ---
-:::ultralytics.nn.autobackend.AutoBackend
+### ::: ultralytics.nn.autobackend.AutoBackend
 <br><br>
 
-# check_class_names
+## check_class_names
 ---
-:::ultralytics.nn.autobackend.check_class_names
+### ::: ultralytics.nn.autobackend.check_class_names
 <br><br>

docs/reference/nn/autoshape.md

@@ -3,12 +3,12 @@ description: Detect 80+ object categories with bounding box coordinates and clas
 keywords: Ultralytics, YOLO, docs, autoshape, detections, object detection, customized shapes, bounding boxes, computer vision
 ---
 
-# AutoShape
+## AutoShape
 ---
-:::ultralytics.nn.autoshape.AutoShape
+### ::: ultralytics.nn.autoshape.AutoShape
 <br><br>
 
-# Detections
+## Detections
 ---
-:::ultralytics.nn.autoshape.Detections
+### ::: ultralytics.nn.autoshape.Detections
 <br><br>

docs/reference/nn/modules/block.md

@@ -3,87 +3,87 @@ description: Explore ultralytics.nn.modules.block to build powerful YOLO object
 keywords: Ultralytics, NN Modules, Blocks, DFL, HGStem, SPP, C1, C2f, C3x, C3TR, GhostBottleneck, BottleneckCSP, Computer Vision
 ---
 
-# DFL
+## DFL
 ---
-:::ultralytics.nn.modules.block.DFL
+### ::: ultralytics.nn.modules.block.DFL
 <br><br>
 
-# Proto
+## Proto
 ---
-:::ultralytics.nn.modules.block.Proto
+### ::: ultralytics.nn.modules.block.Proto
 <br><br>
 
-# HGStem
+## HGStem
 ---
-:::ultralytics.nn.modules.block.HGStem
+### ::: ultralytics.nn.modules.block.HGStem
 <br><br>
 
-# HGBlock
+## HGBlock
 ---
-:::ultralytics.nn.modules.block.HGBlock
+### ::: ultralytics.nn.modules.block.HGBlock
 <br><br>
 
-# SPP
+## SPP
 ---
-:::ultralytics.nn.modules.block.SPP
+### ::: ultralytics.nn.modules.block.SPP
 <br><br>
 
-# SPPF
+## SPPF
 ---
-:::ultralytics.nn.modules.block.SPPF
+### ::: ultralytics.nn.modules.block.SPPF
 <br><br>
 
-# C1
+## C1
 ---
-:::ultralytics.nn.modules.block.C1
+### ::: ultralytics.nn.modules.block.C1
 <br><br>
 
-# C2
+## C2
 ---
-:::ultralytics.nn.modules.block.C2
+### ::: ultralytics.nn.modules.block.C2
 <br><br>
 
-# C2f
+## C2f
 ---
-:::ultralytics.nn.modules.block.C2f
+### ::: ultralytics.nn.modules.block.C2f
 <br><br>
 
-# C3
+## C3
 ---
-:::ultralytics.nn.modules.block.C3
+### ::: ultralytics.nn.modules.block.C3
 <br><br>
 
-# C3x
+## C3x
 ---
-:::ultralytics.nn.modules.block.C3x
+### ::: ultralytics.nn.modules.block.C3x
 <br><br>
 
-# RepC3
+## RepC3
 ---
-:::ultralytics.nn.modules.block.RepC3
+### ::: ultralytics.nn.modules.block.RepC3
 <br><br>
 
-# C3TR
+## C3TR
 ---
-:::ultralytics.nn.modules.block.C3TR
+### ::: ultralytics.nn.modules.block.C3TR
 <br><br>
 
-# C3Ghost
+## C3Ghost
 ---
-:::ultralytics.nn.modules.block.C3Ghost
+### ::: ultralytics.nn.modules.block.C3Ghost
 <br><br>
 
-# GhostBottleneck
+## GhostBottleneck
 ---
-:::ultralytics.nn.modules.block.GhostBottleneck
+### ::: ultralytics.nn.modules.block.GhostBottleneck
 <br><br>
 
-# Bottleneck
+## Bottleneck
 ---
-:::ultralytics.nn.modules.block.Bottleneck
+### ::: ultralytics.nn.modules.block.Bottleneck
 <br><br>
 
-# BottleneckCSP
+## BottleneckCSP
 ---
-:::ultralytics.nn.modules.block.BottleneckCSP
+### ::: ultralytics.nn.modules.block.BottleneckCSP
 <br><br>

docs/reference/nn/modules/conv.md

@@ -3,72 +3,72 @@ description: Explore convolutional neural network modules & techniques such as L
 keywords: Ultralytics, Convolutional Neural Network, Conv2, DWConv, ConvTranspose, GhostConv, ChannelAttention, CBAM, autopad
 ---
 
-# Conv
+## Conv
 ---
-:::ultralytics.nn.modules.conv.Conv
+### ::: ultralytics.nn.modules.conv.Conv
 <br><br>
 
-# Conv2
+## Conv2
 ---
-:::ultralytics.nn.modules.conv.Conv2
+### ::: ultralytics.nn.modules.conv.Conv2
 <br><br>
 
-# LightConv
+## LightConv
 ---
-:::ultralytics.nn.modules.conv.LightConv
+### ::: ultralytics.nn.modules.conv.LightConv
 <br><br>
 
-# DWConv
+## DWConv
 ---
-:::ultralytics.nn.modules.conv.DWConv
+### ::: ultralytics.nn.modules.conv.DWConv
 <br><br>
 
-# DWConvTranspose2d
+## DWConvTranspose2d
 ---
-:::ultralytics.nn.modules.conv.DWConvTranspose2d
+### ::: ultralytics.nn.modules.conv.DWConvTranspose2d
 <br><br>
 
-# ConvTranspose
+## ConvTranspose
 ---
-:::ultralytics.nn.modules.conv.ConvTranspose
+### ::: ultralytics.nn.modules.conv.ConvTranspose
 <br><br>
 
-# Focus
+## Focus
 ---
-:::ultralytics.nn.modules.conv.Focus
+### ::: ultralytics.nn.modules.conv.Focus
 <br><br>
 
-# GhostConv
+## GhostConv
 ---
-:::ultralytics.nn.modules.conv.GhostConv
+### ::: ultralytics.nn.modules.conv.GhostConv
 <br><br>
 
-# RepConv
+## RepConv
 ---
-:::ultralytics.nn.modules.conv.RepConv
+### ::: ultralytics.nn.modules.conv.RepConv
 <br><br>
 
-# ChannelAttention
+## ChannelAttention
 ---
-:::ultralytics.nn.modules.conv.ChannelAttention
+### ::: ultralytics.nn.modules.conv.ChannelAttention
 <br><br>
 
-# SpatialAttention
+## SpatialAttention
 ---
-:::ultralytics.nn.modules.conv.SpatialAttention
+### ::: ultralytics.nn.modules.conv.SpatialAttention
 <br><br>
 
-# CBAM
+## CBAM
 ---
-:::ultralytics.nn.modules.conv.CBAM
+### ::: ultralytics.nn.modules.conv.CBAM
 <br><br>
 
-# Concat
+## Concat
 ---
-:::ultralytics.nn.modules.conv.Concat
+### ::: ultralytics.nn.modules.conv.Concat
 <br><br>
 
-# autopad
+## autopad
 ---
-:::ultralytics.nn.modules.conv.autopad
+### ::: ultralytics.nn.modules.conv.autopad
 <br><br>

docs/reference/nn/modules/head.md

@@ -3,27 +3,27 @@ description: 'Learn about Ultralytics YOLO modules: Segment, Classify, and RTDET
 keywords: Ultralytics, YOLO, object detection, pose estimation, RTDETRDecoder, modules, classes, documentation
 ---
 
-# Detect
+## Detect
 ---
-:::ultralytics.nn.modules.head.Detect
+### ::: ultralytics.nn.modules.head.Detect
 <br><br>
 
-# Segment
+## Segment
 ---
-:::ultralytics.nn.modules.head.Segment
+### ::: ultralytics.nn.modules.head.Segment
 <br><br>
 
-# Pose
+## Pose
 ---
-:::ultralytics.nn.modules.head.Pose
+### ::: ultralytics.nn.modules.head.Pose
 <br><br>
 
-# Classify
+## Classify
 ---
-:::ultralytics.nn.modules.head.Classify
+### ::: ultralytics.nn.modules.head.Classify
 <br><br>
 
-# RTDETRDecoder
+## RTDETRDecoder
 ---
-:::ultralytics.nn.modules.head.RTDETRDecoder
+### ::: ultralytics.nn.modules.head.RTDETRDecoder
 <br><br>

docs/reference/nn/modules/transformer.md

@@ -3,52 +3,52 @@ description: Explore the Ultralytics nn modules pages on Transformer and MLP blo
 keywords: Ultralytics, NN Modules, TransformerEncoderLayer, TransformerLayer, MLPBlock, LayerNorm2d, DeformableTransformerDecoderLayer, examples, code snippets, tutorials
 ---
 
-# TransformerEncoderLayer
+## TransformerEncoderLayer
 ---
-:::ultralytics.nn.modules.transformer.TransformerEncoderLayer
+### ::: ultralytics.nn.modules.transformer.TransformerEncoderLayer
 <br><br>
 
-# AIFI
+## AIFI
 ---
-:::ultralytics.nn.modules.transformer.AIFI
+### ::: ultralytics.nn.modules.transformer.AIFI
 <br><br>
 
-# TransformerLayer
+## TransformerLayer
 ---
-:::ultralytics.nn.modules.transformer.TransformerLayer
+### ::: ultralytics.nn.modules.transformer.TransformerLayer
 <br><br>
 
-# TransformerBlock
+## TransformerBlock
 ---
-:::ultralytics.nn.modules.transformer.TransformerBlock
+### ::: ultralytics.nn.modules.transformer.TransformerBlock
 <br><br>
 
-# MLPBlock
+## MLPBlock
 ---
-:::ultralytics.nn.modules.transformer.MLPBlock
+### ::: ultralytics.nn.modules.transformer.MLPBlock
 <br><br>
 
-# MLP
+## MLP
 ---
-:::ultralytics.nn.modules.transformer.MLP
+### ::: ultralytics.nn.modules.transformer.MLP
 <br><br>
 
-# LayerNorm2d
+## LayerNorm2d
 ---
-:::ultralytics.nn.modules.transformer.LayerNorm2d
+### ::: ultralytics.nn.modules.transformer.LayerNorm2d
 <br><br>
 
-# MSDeformAttn
+## MSDeformAttn
 ---
-:::ultralytics.nn.modules.transformer.MSDeformAttn
+### ::: ultralytics.nn.modules.transformer.MSDeformAttn
 <br><br>
 
-# DeformableTransformerDecoderLayer
+## DeformableTransformerDecoderLayer
 ---
-:::ultralytics.nn.modules.transformer.DeformableTransformerDecoderLayer
+### ::: ultralytics.nn.modules.transformer.DeformableTransformerDecoderLayer
 <br><br>
 
-# DeformableTransformerDecoder
+## DeformableTransformerDecoder
 ---
-:::ultralytics.nn.modules.transformer.DeformableTransformerDecoder
+### ::: ultralytics.nn.modules.transformer.DeformableTransformerDecoder
 <br><br>

docs/reference/nn/modules/utils.md

@@ -3,27 +3,27 @@ description: 'Learn about Ultralytics NN modules: get_clones, linear_init_, and
 keywords: Ultralytics, NN Utils, Docs, PyTorch, bias initialization, linear initialization, multi-scale deformable attention
 ---
 
-# _get_clones
+## _get_clones
 ---
-:::ultralytics.nn.modules.utils._get_clones
+### ::: ultralytics.nn.modules.utils._get_clones
 <br><br>
 
-# bias_init_with_prob
+## bias_init_with_prob
 ---
-:::ultralytics.nn.modules.utils.bias_init_with_prob
+### ::: ultralytics.nn.modules.utils.bias_init_with_prob
 <br><br>
 
-# linear_init_
+## linear_init_
 ---
-:::ultralytics.nn.modules.utils.linear_init_
+### ::: ultralytics.nn.modules.utils.linear_init_
 <br><br>
 
-# inverse_sigmoid
+## inverse_sigmoid
 ---
-:::ultralytics.nn.modules.utils.inverse_sigmoid
+### ::: ultralytics.nn.modules.utils.inverse_sigmoid
 <br><br>
 
-# multi_scale_deformable_attn_pytorch
+## multi_scale_deformable_attn_pytorch
 ---
-:::ultralytics.nn.modules.utils.multi_scale_deformable_attn_pytorch
+### ::: ultralytics.nn.modules.utils.multi_scale_deformable_attn_pytorch
 <br><br>

docs/reference/nn/tasks.md

@@ -3,72 +3,72 @@ description: Learn how to work with Ultralytics YOLO Detection, Segmentation & C
 keywords: neural network, deep learning, computer vision, object detection, image segmentation, image classification, model ensemble, PyTorch
 ---
 
-# BaseModel
+## BaseModel
 ---
-:::ultralytics.nn.tasks.BaseModel
+### ::: ultralytics.nn.tasks.BaseModel
 <br><br>
 
-# DetectionModel
+## DetectionModel
 ---
-:::ultralytics.nn.tasks.DetectionModel
+### ::: ultralytics.nn.tasks.DetectionModel
 <br><br>
 
-# SegmentationModel
+## SegmentationModel
 ---
-:::ultralytics.nn.tasks.SegmentationModel
+### ::: ultralytics.nn.tasks.SegmentationModel
 <br><br>
 
-# PoseModel
+## PoseModel
 ---
-:::ultralytics.nn.tasks.PoseModel
+### ::: ultralytics.nn.tasks.PoseModel
 <br><br>
 
-# ClassificationModel
+## ClassificationModel
 ---
-:::ultralytics.nn.tasks.ClassificationModel
+### ::: ultralytics.nn.tasks.ClassificationModel
 <br><br>
 
-# RTDETRDetectionModel
+## RTDETRDetectionModel
 ---
-:::ultralytics.nn.tasks.RTDETRDetectionModel
+### ::: ultralytics.nn.tasks.RTDETRDetectionModel
 <br><br>
 
-# Ensemble
+## Ensemble
 ---
-:::ultralytics.nn.tasks.Ensemble
+### ::: ultralytics.nn.tasks.Ensemble
 <br><br>
 
-# torch_safe_load
+## torch_safe_load
 ---
-:::ultralytics.nn.tasks.torch_safe_load
+### ::: ultralytics.nn.tasks.torch_safe_load
 <br><br>
 
-# attempt_load_weights
+## attempt_load_weights
 ---
-:::ultralytics.nn.tasks.attempt_load_weights
+### ::: ultralytics.nn.tasks.attempt_load_weights
 <br><br>
 
-# attempt_load_one_weight
+## attempt_load_one_weight
 ---
-:::ultralytics.nn.tasks.attempt_load_one_weight
+### ::: ultralytics.nn.tasks.attempt_load_one_weight
 <br><br>
 
-# parse_model
+## parse_model
 ---
-:::ultralytics.nn.tasks.parse_model
+### ::: ultralytics.nn.tasks.parse_model
 <br><br>
 
-# yaml_model_load
+## yaml_model_load
 ---
-:::ultralytics.nn.tasks.yaml_model_load
+### ::: ultralytics.nn.tasks.yaml_model_load
 <br><br>
 
-# guess_model_scale
+## guess_model_scale
 ---
-:::ultralytics.nn.tasks.guess_model_scale
+### ::: ultralytics.nn.tasks.guess_model_scale
 <br><br>
 
-# guess_model_task
+## guess_model_task
 ---
-:::ultralytics.nn.tasks.guess_model_task
+### ::: ultralytics.nn.tasks.guess_model_task
 <br><br>

docs/reference/tracker/track.md

@@ -3,17 +3,17 @@ description: Learn how to register custom event-tracking and track predictions w
 keywords: Ultralytics YOLO, tracker registration, on_predict_start, object detection
 ---
 
-# on_predict_start
+## on_predict_start
 ---
-:::ultralytics.tracker.track.on_predict_start
+### ::: ultralytics.tracker.track.on_predict_start
 <br><br>
 
-# on_predict_postprocess_end
+## on_predict_postprocess_end
 ---
-:::ultralytics.tracker.track.on_predict_postprocess_end
+### ::: ultralytics.tracker.track.on_predict_postprocess_end
 <br><br>
 
-# register_tracker
+## register_tracker
 ---
-:::ultralytics.tracker.track.register_tracker
+### ::: ultralytics.tracker.track.register_tracker
 <br><br>

docs/reference/tracker/trackers/basetrack.md

@@ -3,12 +3,12 @@ description: 'TrackState: A comprehensive guide to Ultralytics tracker''s BaseTr
 keywords: object detection, object tracking, Ultralytics YOLO, TrackState, workflow improvement
 ---
 
-# TrackState
+## TrackState
 ---
-:::ultralytics.tracker.trackers.basetrack.TrackState
+### ::: ultralytics.tracker.trackers.basetrack.TrackState
 <br><br>
 
-# BaseTrack
+## BaseTrack
 ---
-:::ultralytics.tracker.trackers.basetrack.BaseTrack
+### ::: ultralytics.tracker.trackers.basetrack.BaseTrack
 <br><br>

docs/reference/tracker/trackers/bot_sort.md

@@ -3,12 +3,12 @@ description: '"Optimize tracking with Ultralytics BOTrack. Easily sort and track
 keywords: BOTrack, Ultralytics YOLO Docs, features, usage
 ---
 
-# BOTrack
+## BOTrack
 ---
-:::ultralytics.tracker.trackers.bot_sort.BOTrack
+### ::: ultralytics.tracker.trackers.bot_sort.BOTrack
 <br><br>
 
-# BOTSORT
+## BOTSORT
 ---
-:::ultralytics.tracker.trackers.bot_sort.BOTSORT
+### ::: ultralytics.tracker.trackers.bot_sort.BOTSORT
 <br><br>

docs/reference/tracker/trackers/byte_tracker.md

@@ -3,12 +3,12 @@ description: Learn how to track ByteAI model sizes and tips for model optimizati
 keywords: Byte Tracker, Ultralytics STrack, application monitoring, bytes sent, bytes received, code examples, setup instructions
 ---
 
-# STrack
+## STrack
 ---
-:::ultralytics.tracker.trackers.byte_tracker.STrack
+### ::: ultralytics.tracker.trackers.byte_tracker.STrack
 <br><br>
 
-# BYTETracker
+## BYTETracker
 ---
-:::ultralytics.tracker.trackers.byte_tracker.BYTETracker
+### ::: ultralytics.tracker.trackers.byte_tracker.BYTETracker
 <br><br>

docs/reference/tracker/utils/gmc.md

@@ -3,7 +3,7 @@ description: '"Track Google Marketing Campaigns in GMC with Ultralytics Tracker.
 keywords: Ultralytics, YOLO, object detection, tracker, optimization, models, documentation
 ---
 
-# GMC
+## GMC
 ---
-:::ultralytics.tracker.utils.gmc.GMC
+### ::: ultralytics.tracker.utils.gmc.GMC
 <br><br>

docs/reference/tracker/utils/kalman_filter.md

@@ -3,12 +3,12 @@ description: Improve object tracking with KalmanFilterXYAH in Ultralytics YOLO -
 keywords: KalmanFilterXYAH, Ultralytics Docs, Kalman filter algorithm, object tracking, computer vision, YOLO
 ---
 
-# KalmanFilterXYAH
+## KalmanFilterXYAH
 ---
-:::ultralytics.tracker.utils.kalman_filter.KalmanFilterXYAH
+### ::: ultralytics.tracker.utils.kalman_filter.KalmanFilterXYAH
 <br><br>
 
-# KalmanFilterXYWH
+## KalmanFilterXYWH
 ---
-:::ultralytics.tracker.utils.kalman_filter.KalmanFilterXYWH
+### ::: ultralytics.tracker.utils.kalman_filter.KalmanFilterXYWH
 <br><br>

docs/reference/tracker/utils/matching.md

@@ -3,62 +3,62 @@ description: Learn how to match and fuse object detections for accurate target t
 keywords: Ultralytics, multi-object tracking, object tracking, detection, recognition, matching, indices, iou distance, gate cost matrix, fuse iou, bbox ious
 ---
 
-# merge_matches
+## merge_matches
 ---
-:::ultralytics.tracker.utils.matching.merge_matches
+### ::: ultralytics.tracker.utils.matching.merge_matches
 <br><br>
 
-# _indices_to_matches
+## _indices_to_matches
 ---
-:::ultralytics.tracker.utils.matching._indices_to_matches
+### ::: ultralytics.tracker.utils.matching._indices_to_matches
 <br><br>
 
-# linear_assignment
+## linear_assignment
 ---
-:::ultralytics.tracker.utils.matching.linear_assignment
+### ::: ultralytics.tracker.utils.matching.linear_assignment
 <br><br>
 
-# ious
+## ious
 ---
-:::ultralytics.tracker.utils.matching.ious
+### ::: ultralytics.tracker.utils.matching.ious
 <br><br>
 
-# iou_distance
+## iou_distance
 ---
-:::ultralytics.tracker.utils.matching.iou_distance
+### ::: ultralytics.tracker.utils.matching.iou_distance
 <br><br>
 
-# v_iou_distance
+## v_iou_distance
 ---
-:::ultralytics.tracker.utils.matching.v_iou_distance
+### ::: ultralytics.tracker.utils.matching.v_iou_distance
 <br><br>
 
-# embedding_distance
+## embedding_distance
 ---
-:::ultralytics.tracker.utils.matching.embedding_distance
+### ::: ultralytics.tracker.utils.matching.embedding_distance
 <br><br>
 
-# gate_cost_matrix
+## gate_cost_matrix
 ---
-:::ultralytics.tracker.utils.matching.gate_cost_matrix
+### ::: ultralytics.tracker.utils.matching.gate_cost_matrix
 <br><br>
 
-# fuse_motion
+## fuse_motion
 ---
-:::ultralytics.tracker.utils.matching.fuse_motion
+### ::: ultralytics.tracker.utils.matching.fuse_motion
 <br><br>
 
-# fuse_iou
+## fuse_iou
 ---
-:::ultralytics.tracker.utils.matching.fuse_iou
+### ::: ultralytics.tracker.utils.matching.fuse_iou
 <br><br>
 
-# fuse_score
+## fuse_score
 ---
-:::ultralytics.tracker.utils.matching.fuse_score
+### ::: ultralytics.tracker.utils.matching.fuse_score
 <br><br>
 
-# bbox_ious
+## bbox_ious
 ---
-:::ultralytics.tracker.utils.matching.bbox_ious
+### ::: ultralytics.tracker.utils.matching.bbox_ious
 <br><br>

docs/reference/yolo/cfg/__init__.md

@@ -3,47 +3,47 @@ description: Explore Ultralytics YOLO's configuration functions and tools. Handl
 keywords: Ultralytics, YOLO, configuration, cfg2dict, get_cfg, handle_deprecation, check_cfg_mismatch, merge_equals_args, handle_yolo_hub, handle_yolo_settings, entrypoint, copy_default_cfg
 ---
 
-# cfg2dict
+## cfg2dict
 ---
-:::ultralytics.yolo.cfg.cfg2dict
+### ::: ultralytics.yolo.cfg.cfg2dict
 <br><br>
 
-# get_cfg
+## get_cfg
 ---
-:::ultralytics.yolo.cfg.get_cfg
+### ::: ultralytics.yolo.cfg.get_cfg
 <br><br>
 
-# _handle_deprecation
+## _handle_deprecation
 ---
-:::ultralytics.yolo.cfg._handle_deprecation
+### ::: ultralytics.yolo.cfg._handle_deprecation
 <br><br>
 
-# check_cfg_mismatch
+## check_cfg_mismatch
 ---
-:::ultralytics.yolo.cfg.check_cfg_mismatch
+### ::: ultralytics.yolo.cfg.check_cfg_mismatch
 <br><br>
 
-# merge_equals_args
+## merge_equals_args
 ---
-:::ultralytics.yolo.cfg.merge_equals_args
+### ::: ultralytics.yolo.cfg.merge_equals_args
 <br><br>
 
-# handle_yolo_hub
+## handle_yolo_hub
 ---
-:::ultralytics.yolo.cfg.handle_yolo_hub
+### ::: ultralytics.yolo.cfg.handle_yolo_hub
 <br><br>
 
-# handle_yolo_settings
+## handle_yolo_settings
 ---
-:::ultralytics.yolo.cfg.handle_yolo_settings
+### ::: ultralytics.yolo.cfg.handle_yolo_settings
 <br><br>
 
-# entrypoint
+## entrypoint
 ---
-:::ultralytics.yolo.cfg.entrypoint
+### ::: ultralytics.yolo.cfg.entrypoint
 <br><br>
 
-# copy_default_cfg
+## copy_default_cfg
 ---
-:::ultralytics.yolo.cfg.copy_default_cfg
+### ::: ultralytics.yolo.cfg.copy_default_cfg
 <br><br>

docs/reference/yolo/data/annotator.md

@@ -3,7 +3,7 @@ description: Learn how to use auto_annotate in Ultralytics YOLO to generate anno
 keywords: Ultralytics YOLO, Auto Annotator, AI, image annotation, object detection, labelling, tool
 ---
 
-# auto_annotate
+## auto_annotate
 ---
-:::ultralytics.yolo.data.annotator.auto_annotate
+### ::: ultralytics.yolo.data.annotator.auto_annotate
 <br><br>

docs/reference/yolo/data/augment.md

@@ -3,97 +3,97 @@ description: Use Ultralytics YOLO Data Augmentation transforms with Base, MixUp,
 keywords: YOLO, data augmentation, transforms, BaseTransform, MixUp, RandomHSV, Albumentations, ToTensor, classify_transforms, classify_albumentations
 ---
 
-# BaseTransform
+## BaseTransform
 ---
-:::ultralytics.yolo.data.augment.BaseTransform
+### ::: ultralytics.yolo.data.augment.BaseTransform
 <br><br>
 
-# Compose
+## Compose
 ---
-:::ultralytics.yolo.data.augment.Compose
+### ::: ultralytics.yolo.data.augment.Compose
 <br><br>
 
-# BaseMixTransform
+## BaseMixTransform
 ---
-:::ultralytics.yolo.data.augment.BaseMixTransform
+### ::: ultralytics.yolo.data.augment.BaseMixTransform
 <br><br>
 
-# Mosaic
+## Mosaic
 ---
-:::ultralytics.yolo.data.augment.Mosaic
+### ::: ultralytics.yolo.data.augment.Mosaic
 <br><br>
 
-# MixUp
+## MixUp
 ---
-:::ultralytics.yolo.data.augment.MixUp
+### ::: ultralytics.yolo.data.augment.MixUp
 <br><br>
 
-# RandomPerspective
+## RandomPerspective
 ---
-:::ultralytics.yolo.data.augment.RandomPerspective
+### ::: ultralytics.yolo.data.augment.RandomPerspective
 <br><br>
 
-# RandomHSV
+## RandomHSV
 ---
-:::ultralytics.yolo.data.augment.RandomHSV
+### ::: ultralytics.yolo.data.augment.RandomHSV
 <br><br>
 
-# RandomFlip
+## RandomFlip
 ---
-:::ultralytics.yolo.data.augment.RandomFlip
+### ::: ultralytics.yolo.data.augment.RandomFlip
 <br><br>
 
-# LetterBox
+## LetterBox
 ---
-:::ultralytics.yolo.data.augment.LetterBox
+### ::: ultralytics.yolo.data.augment.LetterBox
 <br><br>
 
-# CopyPaste
+## CopyPaste
 ---
-:::ultralytics.yolo.data.augment.CopyPaste
+### ::: ultralytics.yolo.data.augment.CopyPaste
 <br><br>
 
-# Albumentations
+## Albumentations
 ---
-:::ultralytics.yolo.data.augment.Albumentations
+### ::: ultralytics.yolo.data.augment.Albumentations
 <br><br>
 
-# Format
+## Format
 ---
-:::ultralytics.yolo.data.augment.Format
+### ::: ultralytics.yolo.data.augment.Format
 <br><br>
 
-# ClassifyLetterBox
+## ClassifyLetterBox
 ---
-:::ultralytics.yolo.data.augment.ClassifyLetterBox
+### ::: ultralytics.yolo.data.augment.ClassifyLetterBox
 <br><br>
 
-# CenterCrop
+## CenterCrop
 ---
-:::ultralytics.yolo.data.augment.CenterCrop
+### ::: ultralytics.yolo.data.augment.CenterCrop
 <br><br>
 
-# ToTensor
+## ToTensor
 ---
-:::ultralytics.yolo.data.augment.ToTensor
+### ::: ultralytics.yolo.data.augment.ToTensor
 <br><br>
 
-# v8_transforms
+## v8_transforms
 ---
-:::ultralytics.yolo.data.augment.v8_transforms
+### ::: ultralytics.yolo.data.augment.v8_transforms
 <br><br>
 
-# classify_transforms
+## classify_transforms
 ---
-:::ultralytics.yolo.data.augment.classify_transforms
+### ::: ultralytics.yolo.data.augment.classify_transforms
 <br><br>
 
-# hsv2colorjitter
+## hsv2colorjitter
 ---
-:::ultralytics.yolo.data.augment.hsv2colorjitter
+### ::: ultralytics.yolo.data.augment.hsv2colorjitter
 <br><br>
 
-# classify_albumentations
+## classify_albumentations
 ---
-:::ultralytics.yolo.data.augment.classify_albumentations
+### ::: ultralytics.yolo.data.augment.classify_albumentations
 <br><br>

docs/reference/yolo/data/base.md

@@ -3,7 +3,7 @@ description: Learn about BaseDataset in Ultralytics YOLO, a flexible dataset cla
 keywords: BaseDataset, Ultralytics YOLO, object detection, real-world applications, documentation
 ---
 
-# BaseDataset
+## BaseDataset
 ---
-:::ultralytics.yolo.data.base.BaseDataset
+### ::: ultralytics.yolo.data.base.BaseDataset
 <br><br>

docs/reference/yolo/data/build.md

@@ -3,37 +3,37 @@ description: Maximize YOLO performance with Ultralytics' InfiniteDataLoader, see
 keywords: Ultralytics, YOLO, object detection, data loading, build dataloader, load inference source
 ---
 
-# InfiniteDataLoader
+## InfiniteDataLoader
 ---
-:::ultralytics.yolo.data.build.InfiniteDataLoader
+### ::: ultralytics.yolo.data.build.InfiniteDataLoader
 <br><br>
 
-# _RepeatSampler
+## _RepeatSampler
 ---
-:::ultralytics.yolo.data.build._RepeatSampler
+### ::: ultralytics.yolo.data.build._RepeatSampler
 <br><br>
 
-# seed_worker
+## seed_worker
 ---
-:::ultralytics.yolo.data.build.seed_worker
+### ::: ultralytics.yolo.data.build.seed_worker
 <br><br>
 
-# build_yolo_dataset
+## build_yolo_dataset
 ---
-:::ultralytics.yolo.data.build.build_yolo_dataset
+### ::: ultralytics.yolo.data.build.build_yolo_dataset
 <br><br>
 
-# build_dataloader
+## build_dataloader
 ---
-:::ultralytics.yolo.data.build.build_dataloader
+### ::: ultralytics.yolo.data.build.build_dataloader
 <br><br>
 
-# check_source
+## check_source
 ---
-:::ultralytics.yolo.data.build.check_source
+### ::: ultralytics.yolo.data.build.check_source
 <br><br>
 
-# load_inference_source
+## load_inference_source
 ---
-:::ultralytics.yolo.data.build.load_inference_source
+### ::: ultralytics.yolo.data.build.load_inference_source
 <br><br>

docs/reference/yolo/data/converter.md

@@ -3,32 +3,32 @@ description: Convert COCO-91 to COCO-80 class, RLE to polygon, and merge multi-s
 keywords: Ultralytics, YOLO, converter, COCO91, COCO80, rle2polygon, merge_multi_segment, annotations
 ---
 
-# coco91_to_coco80_class
+## coco91_to_coco80_class
 ---
-:::ultralytics.yolo.data.converter.coco91_to_coco80_class
+### ::: ultralytics.yolo.data.converter.coco91_to_coco80_class
 <br><br>
 
-# convert_coco
+## convert_coco
 ---
-:::ultralytics.yolo.data.converter.convert_coco
+### ::: ultralytics.yolo.data.converter.convert_coco
 <br><br>
 
-# rle2polygon
+## rle2polygon
 ---
-:::ultralytics.yolo.data.converter.rle2polygon
+### ::: ultralytics.yolo.data.converter.rle2polygon
 <br><br>
 
-# min_index
+## min_index
 ---
-:::ultralytics.yolo.data.converter.min_index
+### ::: ultralytics.yolo.data.converter.min_index
 <br><br>
 
-# merge_multi_segment
+## merge_multi_segment
 ---
-:::ultralytics.yolo.data.converter.merge_multi_segment
+### ::: ultralytics.yolo.data.converter.merge_multi_segment
 <br><br>
 
-# delete_dsstore
+## delete_dsstore
 ---
-:::ultralytics.yolo.data.converter.delete_dsstore
+### ::: ultralytics.yolo.data.converter.delete_dsstore
 <br><br>

docs/reference/yolo/data/dataloaders/stream_loaders.md

@@ -3,42 +3,42 @@ description: 'Ultralytics YOLO Docs: Learn about stream loaders for image and te
 keywords: Ultralytics YOLO, data loaders, stream load images, screenshots, tensor data, autocast list, youtube URL retriever
 ---
 
-# SourceTypes
+## SourceTypes
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.SourceTypes
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.SourceTypes
 <br><br>
 
-# LoadStreams
+## LoadStreams
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadStreams
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.LoadStreams
 <br><br>
 
-# LoadScreenshots
+## LoadScreenshots
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadScreenshots
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.LoadScreenshots
 <br><br>
 
-# LoadImages
+## LoadImages
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadImages
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.LoadImages
 <br><br>
 
-# LoadPilAndNumpy
+## LoadPilAndNumpy
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadPilAndNumpy
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.LoadPilAndNumpy
 <br><br>
 
-# LoadTensor
+## LoadTensor
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadTensor
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.LoadTensor
 <br><br>
 
-# autocast_list
+## autocast_list
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.autocast_list
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.autocast_list
 <br><br>
 
-# get_best_youtube_url
+## get_best_youtube_url
 ---
-:::ultralytics.yolo.data.dataloaders.stream_loaders.get_best_youtube_url
+### ::: ultralytics.yolo.data.dataloaders.stream_loaders.get_best_youtube_url
 <br><br>

docs/reference/yolo/data/dataloaders/v5augmentations.md

@@ -3,87 +3,87 @@ description: Enhance image data with Albumentations CenterCrop, normalize, augme
 keywords: YOLO, object detection, data loaders, V5 augmentations, CenterCrop, normalize, random_perspective
 ---
 
-# Albumentations
+## Albumentations
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.Albumentations
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.Albumentations
 <br><br>
 
-# LetterBox
+## LetterBox
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.LetterBox
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.LetterBox
 <br><br>
 
-# CenterCrop
+## CenterCrop
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.CenterCrop
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.CenterCrop
 <br><br>
 
-# ToTensor
+## ToTensor
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.ToTensor
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.ToTensor
 <br><br>
 
-# normalize
+## normalize
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.normalize
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.normalize
 <br><br>
 
-# denormalize
+## denormalize
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.denormalize
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.denormalize
 <br><br>
 
-# augment_hsv
+## augment_hsv
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.augment_hsv
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.augment_hsv
 <br><br>
 
-# hist_equalize
+## hist_equalize
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.hist_equalize
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.hist_equalize
 <br><br>
 
-# replicate
+## replicate
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.replicate
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.replicate
 <br><br>
 
-# letterbox
+## letterbox
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.letterbox
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.letterbox
 <br><br>
 
-# random_perspective
+## random_perspective
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.random_perspective
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.random_perspective
 <br><br>
 
-# copy_paste
+## copy_paste
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.copy_paste
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.copy_paste
 <br><br>
 
-# cutout
+## cutout
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.cutout
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.cutout
 <br><br>
 
-# mixup
+## mixup
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.mixup
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.mixup
 <br><br>
 
-# box_candidates
+## box_candidates
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.box_candidates
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.box_candidates
 <br><br>
 
-# classify_albumentations
+## classify_albumentations
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.classify_albumentations
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.classify_albumentations
 <br><br>
 
-# classify_transforms
+## classify_transforms
 ---
-:::ultralytics.yolo.data.dataloaders.v5augmentations.classify_transforms
+### ::: ultralytics.yolo.data.dataloaders.v5augmentations.classify_transforms
 <br><br>

docs/reference/yolo/data/dataloaders/v5loader.md

@@ -3,92 +3,92 @@ description: Efficiently load images and labels to models using Ultralytics YOLO
 keywords: YOLO, data loader, image classification, object detection, Ultralytics
 ---
 
-# InfiniteDataLoader
+## InfiniteDataLoader
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.InfiniteDataLoader
+### ::: ultralytics.yolo.data.dataloaders.v5loader.InfiniteDataLoader
 <br><br>
 
-# _RepeatSampler
+## _RepeatSampler
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader._RepeatSampler
+### ::: ultralytics.yolo.data.dataloaders.v5loader._RepeatSampler
 <br><br>
 
-# LoadScreenshots
+## LoadScreenshots
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.LoadScreenshots
+### ::: ultralytics.yolo.data.dataloaders.v5loader.LoadScreenshots
 <br><br>
 
-# LoadImages
+## LoadImages
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.LoadImages
+### ::: ultralytics.yolo.data.dataloaders.v5loader.LoadImages
 <br><br>
 
-# LoadStreams
+## LoadStreams
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.LoadStreams
+### ::: ultralytics.yolo.data.dataloaders.v5loader.LoadStreams
 <br><br>
 
-# LoadImagesAndLabels
+## LoadImagesAndLabels
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.LoadImagesAndLabels
+### ::: ultralytics.yolo.data.dataloaders.v5loader.LoadImagesAndLabels
 <br><br>
 
-# ClassificationDataset
+## ClassificationDataset
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.ClassificationDataset
+### ::: ultralytics.yolo.data.dataloaders.v5loader.ClassificationDataset
 <br><br>
 
-# get_hash
+## get_hash
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.get_hash
+### ::: ultralytics.yolo.data.dataloaders.v5loader.get_hash
 <br><br>
 
-# exif_size
+## exif_size
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.exif_size
+### ::: ultralytics.yolo.data.dataloaders.v5loader.exif_size
 <br><br>
 
-# exif_transpose
+## exif_transpose
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.exif_transpose
+### ::: ultralytics.yolo.data.dataloaders.v5loader.exif_transpose
 <br><br>
 
-# seed_worker
+## seed_worker
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.seed_worker
+### ::: ultralytics.yolo.data.dataloaders.v5loader.seed_worker
 <br><br>
 
-# create_dataloader
+## create_dataloader
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.create_dataloader
+### ::: ultralytics.yolo.data.dataloaders.v5loader.create_dataloader
 <br><br>
 
-# img2label_paths
+## img2label_paths
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.img2label_paths
+### ::: ultralytics.yolo.data.dataloaders.v5loader.img2label_paths
 <br><br>
 
-# flatten_recursive
+## flatten_recursive
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.flatten_recursive
+### ::: ultralytics.yolo.data.dataloaders.v5loader.flatten_recursive
 <br><br>
 
-# extract_boxes
+## extract_boxes
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.extract_boxes
+### ::: ultralytics.yolo.data.dataloaders.v5loader.extract_boxes
 <br><br>
 
-# autosplit
+## autosplit
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.autosplit
+### ::: ultralytics.yolo.data.dataloaders.v5loader.autosplit
 <br><br>
 
-# verify_image_label
+## verify_image_label
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.verify_image_label
+### ::: ultralytics.yolo.data.dataloaders.v5loader.verify_image_label
 <br><br>
 
-# create_classification_dataloader
+## create_classification_dataloader
 ---
-:::ultralytics.yolo.data.dataloaders.v5loader.create_classification_dataloader
+### ::: ultralytics.yolo.data.dataloaders.v5loader.create_classification_dataloader
 <br><br>

docs/reference/yolo/data/dataset.md

@@ -3,17 +3,17 @@ description: Create custom YOLOv5 datasets with Ultralytics YOLODataset and Sema
 keywords: YOLODataset, SemanticDataset, Ultralytics YOLO Docs, Object Detection, Segmentation
 ---
 
-# YOLODataset
+## YOLODataset
 ---
-:::ultralytics.yolo.data.dataset.YOLODataset
+### ::: ultralytics.yolo.data.dataset.YOLODataset
 <br><br>
 
-# ClassificationDataset
+## ClassificationDataset
 ---
-:::ultralytics.yolo.data.dataset.ClassificationDataset
+### ::: ultralytics.yolo.data.dataset.ClassificationDataset
 <br><br>
 
-# SemanticDataset
+## SemanticDataset
 ---
-:::ultralytics.yolo.data.dataset.SemanticDataset
+### ::: ultralytics.yolo.data.dataset.SemanticDataset
 <br><br>

docs/reference/yolo/data/dataset_wrappers.md

@@ -3,7 +3,7 @@ description: Create a custom dataset of mixed and oriented rectangular objects w
 keywords: Ultralytics YOLO, MixAndRectDataset, dataset wrapper, image-level annotations, object-level annotations, rectangular object detection
 ---
 
-# MixAndRectDataset
+## MixAndRectDataset
 ---
-:::ultralytics.yolo.data.dataset_wrappers.MixAndRectDataset
+### ::: ultralytics.yolo.data.dataset_wrappers.MixAndRectDataset
 <br><br>

docs/reference/yolo/data/utils.md

@@ -3,67 +3,67 @@ description: Efficiently handle data in YOLO with Ultralytics. Utilize HUBDatase
 keywords: YOLOv4, Object Detection, Computer Vision, Deep Learning, Convolutional Neural Network, CNN, Ultralytics Docs
 ---
 
-# HUBDatasetStats
+## HUBDatasetStats
 ---
-:::ultralytics.yolo.data.utils.HUBDatasetStats
+### ::: ultralytics.yolo.data.utils.HUBDatasetStats
 <br><br>
 
-# img2label_paths
+## img2label_paths
 ---
-:::ultralytics.yolo.data.utils.img2label_paths
+### ::: ultralytics.yolo.data.utils.img2label_paths
 <br><br>
 
-# get_hash
+## get_hash
 ---
-:::ultralytics.yolo.data.utils.get_hash
+### ::: ultralytics.yolo.data.utils.get_hash
 <br><br>
 
-# exif_size
+## exif_size
 ---
-:::ultralytics.yolo.data.utils.exif_size
+### ::: ultralytics.yolo.data.utils.exif_size
 <br><br>
 
-# verify_image_label
+## verify_image_label
 ---
-:::ultralytics.yolo.data.utils.verify_image_label
+### ::: ultralytics.yolo.data.utils.verify_image_label
 <br><br>
 
-# polygon2mask
+## polygon2mask
 ---
-:::ultralytics.yolo.data.utils.polygon2mask
+### ::: ultralytics.yolo.data.utils.polygon2mask
 <br><br>
 
-# polygons2masks
+## polygons2masks
 ---
-:::ultralytics.yolo.data.utils.polygons2masks
+### ::: ultralytics.yolo.data.utils.polygons2masks
 <br><br>
 
-# polygons2masks_overlap
+## polygons2masks_overlap
 ---
-:::ultralytics.yolo.data.utils.polygons2masks_overlap
+### ::: ultralytics.yolo.data.utils.polygons2masks_overlap
 <br><br>
 
-# check_det_dataset
+## check_det_dataset
 ---
-:::ultralytics.yolo.data.utils.check_det_dataset
+### ::: ultralytics.yolo.data.utils.check_det_dataset
 <br><br>
 
-# check_cls_dataset
+## check_cls_dataset
 ---
-:::ultralytics.yolo.data.utils.check_cls_dataset
+### ::: ultralytics.yolo.data.utils.check_cls_dataset
 <br><br>
 
-# compress_one_image
+## compress_one_image
 ---
-:::ultralytics.yolo.data.utils.compress_one_image
+### ::: ultralytics.yolo.data.utils.compress_one_image
 <br><br>
 
-# delete_dsstore
+## delete_dsstore
 ---
-:::ultralytics.yolo.data.utils.delete_dsstore
+### ::: ultralytics.yolo.data.utils.delete_dsstore
 <br><br>
 
-# zip_directory
+## zip_directory
 ---
-:::ultralytics.yolo.data.utils.zip_directory
+### ::: ultralytics.yolo.data.utils.zip_directory
 <br><br>

docs/reference/yolo/engine/exporter.md

@@ -3,32 +3,32 @@ description: Learn how to export your YOLO model in various formats using Ultral
 keywords: Ultralytics, YOLO, exporter, iOS detect model, gd_outputs, export
 ---
 
-# Exporter
+## Exporter
 ---
-:::ultralytics.yolo.engine.exporter.Exporter
+### ::: ultralytics.yolo.engine.exporter.Exporter
 <br><br>
 
-# iOSDetectModel
+## iOSDetectModel
 ---
-:::ultralytics.yolo.engine.exporter.iOSDetectModel
+### ::: ultralytics.yolo.engine.exporter.iOSDetectModel
 <br><br>
 
-# export_formats
+## export_formats
 ---
-:::ultralytics.yolo.engine.exporter.export_formats
+### ::: ultralytics.yolo.engine.exporter.export_formats
 <br><br>
 
-# gd_outputs
+## gd_outputs
 ---
-:::ultralytics.yolo.engine.exporter.gd_outputs
+### ::: ultralytics.yolo.engine.exporter.gd_outputs
 <br><br>
 
-# try_export
+## try_export
 ---
-:::ultralytics.yolo.engine.exporter.try_export
+### ::: ultralytics.yolo.engine.exporter.try_export
 <br><br>
 
-# export
+## export
 ---
-:::ultralytics.yolo.engine.exporter.export
+### ::: ultralytics.yolo.engine.exporter.export
 <br><br>

docs/reference/yolo/engine/model.md

@@ -3,7 +3,7 @@ description: Discover the YOLO model of Ultralytics engine to simplify your obje
 keywords: YOLO, object detection, model, architecture, usage, customization, Ultralytics Docs
 ---
 
-# YOLO
+## YOLO
 ---
-:::ultralytics.yolo.engine.model.YOLO
+### ::: ultralytics.yolo.engine.model.YOLO
 <br><br>

docs/reference/yolo/engine/predictor.md

@@ -3,7 +3,7 @@ description: '"The BasePredictor class in Ultralytics YOLO Engine predicts objec
 keywords: Ultralytics, YOLO, BasePredictor, Object Detection, Computer Vision, Fast Model, Insights
 ---
 
-# BasePredictor
+## BasePredictor
 ---
-:::ultralytics.yolo.engine.predictor.BasePredictor
+### ::: ultralytics.yolo.engine.predictor.BasePredictor
 <br><br>

docs/reference/yolo/engine/results.md

@@ -3,32 +3,32 @@ description: Learn about BaseTensor & Boxes in Ultralytics YOLO Engine. Check ou
 keywords: YOLO, Engine, Results, Masks, Probs, Ultralytics
 ---
 
-# BaseTensor
+## BaseTensor
 ---
-:::ultralytics.yolo.engine.results.BaseTensor
+### ::: ultralytics.yolo.engine.results.BaseTensor
 <br><br>
 
-# Results
+## Results
 ---
-:::ultralytics.yolo.engine.results.Results
+### ::: ultralytics.yolo.engine.results.Results
 <br><br>
 
-# Boxes
+## Boxes
 ---
-:::ultralytics.yolo.engine.results.Boxes
+### ::: ultralytics.yolo.engine.results.Boxes
 <br><br>
 
-# Masks
+## Masks
 ---
-:::ultralytics.yolo.engine.results.Masks
+### ::: ultralytics.yolo.engine.results.Masks
 <br><br>
 
-# Keypoints
+## Keypoints
 ---
-:::ultralytics.yolo.engine.results.Keypoints
+### ::: ultralytics.yolo.engine.results.Keypoints
 <br><br>
 
-# Probs
+## Probs
 ---
-:::ultralytics.yolo.engine.results.Probs
+### ::: ultralytics.yolo.engine.results.Probs
 <br><br>

docs/reference/yolo/engine/trainer.md

@@ -3,7 +3,7 @@ description: Train faster with mixed precision. Learn how to use BaseTrainer wit
 keywords: Ultralytics YOLO, BaseTrainer, object detection models, training guide
 ---
 
-# BaseTrainer
+## BaseTrainer
 ---
-:::ultralytics.yolo.engine.trainer.BaseTrainer
+### ::: ultralytics.yolo.engine.trainer.BaseTrainer
 <br><br>

docs/reference/yolo/engine/validator.md

@@ -3,7 +3,7 @@ description: Ensure YOLOv5 models meet constraints and standards with the BaseVa
 keywords: Ultralytics, YOLO, BaseValidator, models, validation, object detection
 ---
 
-# BaseValidator
+## BaseValidator
 ---
-:::ultralytics.yolo.engine.validator.BaseValidator
+### ::: ultralytics.yolo.engine.validator.BaseValidator
 <br><br>

docs/reference/yolo/nas/model.md

@@ -3,7 +3,7 @@ description: Learn about the Neural Architecture Search (NAS) feature available
 keywords: Ultralytics YOLO, object detection, NAS, Neural Architecture Search, model optimization, accuracy improvement
 ---
 
-# NAS
+## NAS
 ---
-:::ultralytics.yolo.nas.model.NAS
+### ::: ultralytics.yolo.nas.model.NAS
 <br><br>

docs/reference/yolo/nas/predict.md

@@ -3,7 +3,7 @@ description: Learn how to use NASPredictor in Ultralytics YOLO for deploying eff
 keywords: Ultralytics YOLO, NASPredictor, neural architecture search, efficient CNN models, search algorithms
 ---
 
-# NASPredictor
+## NASPredictor
 ---
-:::ultralytics.yolo.nas.predict.NASPredictor
+### ::: ultralytics.yolo.nas.predict.NASPredictor
 <br><br>

docs/reference/yolo/nas/val.md

@@ -3,7 +3,7 @@ description: Learn about NASValidator in the Ultralytics YOLO Docs. Properly val
 keywords: NASValidator, YOLO, neural architecture search, validation, performance, Ultralytics
 ---
 
-# NASValidator
+## NASValidator
 ---
-:::ultralytics.yolo.nas.val.NASValidator
+### ::: ultralytics.yolo.nas.val.NASValidator
 <br><br>

docs/reference/yolo/utils/__init__.md

@@ -3,167 +3,167 @@ description: Uncover utility functions in Ultralytics YOLO. Handle YAML, threadi
 keywords: Ultralytics, YOLO, utils, SimpleClass, IterableSimpleNamespace, EmojiFilter, TryExcept, plt_settings, set_logging, emojis, yaml_save, yaml_load, yaml_print, is_colab, is_kaggle, is_jupyter, is_docker, is_online, is_pip_package, is_dir_writeable, is_pytest_running, is_github_actions_ci, is_git_dir, get_git_dir, get_git_origin_url, get_git_branch, get_default_args, get_user_config_dir, colorstr, threaded, set_sentry, get_settings, set_settings, deprecation_warn, clean_url, url2file
 ---
 
-# SimpleClass
+## SimpleClass
 ---
-:::ultralytics.yolo.utils.SimpleClass
+### ::: ultralytics.yolo.utils.SimpleClass
 <br><br>
 
-# IterableSimpleNamespace
+## IterableSimpleNamespace
 ---
-:::ultralytics.yolo.utils.IterableSimpleNamespace
+### ::: ultralytics.yolo.utils.IterableSimpleNamespace
 <br><br>
 
-# EmojiFilter
+## EmojiFilter
 ---
-:::ultralytics.yolo.utils.EmojiFilter
+### ::: ultralytics.yolo.utils.EmojiFilter
 <br><br>
 
-# TryExcept
+## TryExcept
 ---
-:::ultralytics.yolo.utils.TryExcept
+### ::: ultralytics.yolo.utils.TryExcept
 <br><br>
 
-# plt_settings
+## plt_settings
 ---
-:::ultralytics.yolo.utils.plt_settings
+### ::: ultralytics.yolo.utils.plt_settings
 <br><br>
 
-# set_logging
+## set_logging
 ---
-:::ultralytics.yolo.utils.set_logging
+### ::: ultralytics.yolo.utils.set_logging
 <br><br>
 
-# emojis
+## emojis
 ---
-:::ultralytics.yolo.utils.emojis
+### ::: ultralytics.yolo.utils.emojis
 <br><br>
 
-# yaml_save
+## yaml_save
 ---
-:::ultralytics.yolo.utils.yaml_save
+### ::: ultralytics.yolo.utils.yaml_save
 <br><br>
 
-# yaml_load
+## yaml_load
 ---
-:::ultralytics.yolo.utils.yaml_load
+### ::: ultralytics.yolo.utils.yaml_load
 <br><br>
 
-# yaml_print
+## yaml_print
 ---
-:::ultralytics.yolo.utils.yaml_print
+### ::: ultralytics.yolo.utils.yaml_print
 <br><br>
 
-# is_colab
+## is_colab
 ---
-:::ultralytics.yolo.utils.is_colab
+### ::: ultralytics.yolo.utils.is_colab
 <br><br>
 
-# is_kaggle
+## is_kaggle
 ---
-:::ultralytics.yolo.utils.is_kaggle
+### ::: ultralytics.yolo.utils.is_kaggle
 <br><br>
 
-# is_jupyter
+## is_jupyter
 ---
-:::ultralytics.yolo.utils.is_jupyter
+### ::: ultralytics.yolo.utils.is_jupyter
 <br><br>
 
-# is_docker
+## is_docker
 ---
-:::ultralytics.yolo.utils.is_docker
+### ::: ultralytics.yolo.utils.is_docker
 <br><br>
 
-# is_online
+## is_online
 ---
-:::ultralytics.yolo.utils.is_online
+### ::: ultralytics.yolo.utils.is_online
 <br><br>
 
-# is_pip_package
+## is_pip_package
 ---
-:::ultralytics.yolo.utils.is_pip_package
+### ::: ultralytics.yolo.utils.is_pip_package
 <br><br>
 
-# is_dir_writeable
+## is_dir_writeable
 ---
-:::ultralytics.yolo.utils.is_dir_writeable
+### ::: ultralytics.yolo.utils.is_dir_writeable
 <br><br>
 
-# is_pytest_running
+## is_pytest_running
 ---
-:::ultralytics.yolo.utils.is_pytest_running
+### ::: ultralytics.yolo.utils.is_pytest_running
 <br><br>
 
-# is_github_actions_ci
+## is_github_actions_ci
 ---
-:::ultralytics.yolo.utils.is_github_actions_ci
+### ::: ultralytics.yolo.utils.is_github_actions_ci
 <br><br>
 
-# is_git_dir
+## is_git_dir
 ---
-:::ultralytics.yolo.utils.is_git_dir
+### ::: ultralytics.yolo.utils.is_git_dir
 <br><br>
 
-# get_git_dir
+## get_git_dir
 ---
-:::ultralytics.yolo.utils.get_git_dir
+### ::: ultralytics.yolo.utils.get_git_dir
 <br><br>
 
-# get_git_origin_url
+## get_git_origin_url
 ---
-:::ultralytics.yolo.utils.get_git_origin_url
+### ::: ultralytics.yolo.utils.get_git_origin_url
 <br><br>
 
-# get_git_branch
+## get_git_branch
 ---
-:::ultralytics.yolo.utils.get_git_branch
+### ::: ultralytics.yolo.utils.get_git_branch
 <br><br>
 
-# get_default_args
+## get_default_args
 ---
-:::ultralytics.yolo.utils.get_default_args
+### ::: ultralytics.yolo.utils.get_default_args
 <br><br>
 
-# get_user_config_dir
+## get_user_config_dir
 ---
-:::ultralytics.yolo.utils.get_user_config_dir
+### ::: ultralytics.yolo.utils.get_user_config_dir
 <br><br>
 
-# colorstr
+## colorstr
 ---
-:::ultralytics.yolo.utils.colorstr
+### ::: ultralytics.yolo.utils.colorstr
 <br><br>
 
-# threaded
+## threaded
 ---
-:::ultralytics.yolo.utils.threaded
+### ::: ultralytics.yolo.utils.threaded
 <br><br>
 
-# set_sentry
+## set_sentry
 ---
-:::ultralytics.yolo.utils.set_sentry
+### ::: ultralytics.yolo.utils.set_sentry
 <br><br>
 
-# get_settings
+## get_settings
 ---
-:::ultralytics.yolo.utils.get_settings
+### ::: ultralytics.yolo.utils.get_settings
 <br><br>
 
-# set_settings
+## set_settings
 ---
-:::ultralytics.yolo.utils.set_settings
+### ::: ultralytics.yolo.utils.set_settings
 <br><br>
 
-# deprecation_warn
+## deprecation_warn
 ---
-:::ultralytics.yolo.utils.deprecation_warn
+### ::: ultralytics.yolo.utils.deprecation_warn
 <br><br>
 
-# clean_url
+## clean_url
 ---
-:::ultralytics.yolo.utils.clean_url
+### ::: ultralytics.yolo.utils.clean_url
 <br><br>
 
-# url2file
+## url2file
 ---
-:::ultralytics.yolo.utils.url2file
+### ::: ultralytics.yolo.utils.url2file
 <br><br>

docs/reference/yolo/utils/autobatch.md

@@ -3,12 +3,12 @@ description: Dynamically adjusts input size to optimize GPU memory usage during
 keywords: YOLOv5, batch size, training, Ultralytics Autobatch, object detection, model performance
 ---
 
-# check_train_batch_size
+## check_train_batch_size
 ---
-:::ultralytics.yolo.utils.autobatch.check_train_batch_size
+### ::: ultralytics.yolo.utils.autobatch.check_train_batch_size
 <br><br>
 
-# autobatch
+## autobatch
 ---
-:::ultralytics.yolo.utils.autobatch.autobatch
+### ::: ultralytics.yolo.utils.autobatch.autobatch
 <br><br>

docs/reference/yolo/utils/benchmarks.md

@@ -3,12 +3,12 @@ description: Improve your YOLO's performance and measure its speed. Benchmark ut
 keywords: Ultralytics YOLO, ProfileModels, benchmark, model inference, detection
 ---
 
-# ProfileModels
+## ProfileModels
 ---
-:::ultralytics.yolo.utils.benchmarks.ProfileModels
+### ::: ultralytics.yolo.utils.benchmarks.ProfileModels
 <br><br>
 
-# benchmark
+## benchmark
 ---
-:::ultralytics.yolo.utils.benchmarks.benchmark
+### ::: ultralytics.yolo.utils.benchmarks.benchmark
 <br><br>

docs/reference/yolo/utils/callbacks/base.md

@@ -3,137 +3,137 @@ description: Learn about YOLO's callback functions from on_train_start to add_in
 keywords: YOLO, Ultralytics, callbacks, object detection, training, inference
 ---
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_pretrain_routine_start
 <br><br>
 
-# on_pretrain_routine_end
+## on_pretrain_routine_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_pretrain_routine_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_pretrain_routine_end
 <br><br>
 
-# on_train_start
+## on_train_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_train_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_train_start
 <br><br>
 
-# on_train_epoch_start
+## on_train_epoch_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_train_epoch_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_train_epoch_start
 <br><br>
 
-# on_train_batch_start
+## on_train_batch_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_train_batch_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_train_batch_start
 <br><br>
 
-# optimizer_step
+## optimizer_step
 ---
-:::ultralytics.yolo.utils.callbacks.base.optimizer_step
+### ::: ultralytics.yolo.utils.callbacks.base.optimizer_step
 <br><br>
 
-# on_before_zero_grad
+## on_before_zero_grad
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_before_zero_grad
+### ::: ultralytics.yolo.utils.callbacks.base.on_before_zero_grad
 <br><br>
 
-# on_train_batch_end
+## on_train_batch_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_train_batch_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_train_batch_end
 <br><br>
 
-# on_train_epoch_end
+## on_train_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_train_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_train_epoch_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_fit_epoch_end
 <br><br>
 
-# on_model_save
+## on_model_save
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_model_save
+### ::: ultralytics.yolo.utils.callbacks.base.on_model_save
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_train_end
 <br><br>
 
-# on_params_update
+## on_params_update
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_params_update
+### ::: ultralytics.yolo.utils.callbacks.base.on_params_update
 <br><br>
 
-# teardown
+## teardown
 ---
-:::ultralytics.yolo.utils.callbacks.base.teardown
+### ::: ultralytics.yolo.utils.callbacks.base.teardown
 <br><br>
 
-# on_val_start
+## on_val_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_val_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_val_start
 <br><br>
 
-# on_val_batch_start
+## on_val_batch_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_val_batch_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_val_batch_start
 <br><br>
 
-# on_val_batch_end
+## on_val_batch_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_val_batch_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_val_batch_end
 <br><br>
 
-# on_val_end
+## on_val_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_val_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_val_end
 <br><br>
 
-# on_predict_start
+## on_predict_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_predict_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_predict_start
 <br><br>
 
-# on_predict_batch_start
+## on_predict_batch_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_predict_batch_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_predict_batch_start
 <br><br>
 
-# on_predict_batch_end
+## on_predict_batch_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_predict_batch_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_predict_batch_end
 <br><br>
 
-# on_predict_postprocess_end
+## on_predict_postprocess_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_predict_postprocess_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_predict_postprocess_end
 <br><br>
 
-# on_predict_end
+## on_predict_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_predict_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_predict_end
 <br><br>
 
-# on_export_start
+## on_export_start
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_export_start
+### ::: ultralytics.yolo.utils.callbacks.base.on_export_start
 <br><br>
 
-# on_export_end
+## on_export_end
 ---
-:::ultralytics.yolo.utils.callbacks.base.on_export_end
+### ::: ultralytics.yolo.utils.callbacks.base.on_export_end
 <br><br>
 
-# get_default_callbacks
+## get_default_callbacks
 ---
-:::ultralytics.yolo.utils.callbacks.base.get_default_callbacks
+### ::: ultralytics.yolo.utils.callbacks.base.get_default_callbacks
 <br><br>
 
-# add_integration_callbacks
+## add_integration_callbacks
 ---
-:::ultralytics.yolo.utils.callbacks.base.add_integration_callbacks
+### ::: ultralytics.yolo.utils.callbacks.base.add_integration_callbacks
 <br><br>

docs/reference/yolo/utils/callbacks/clearml.md

@@ -3,37 +3,37 @@ description: Improve your YOLOv5 model training with callbacks from ClearML. Lea
 keywords: Ultralytics YOLO, callbacks, log plots, epoch monitoring, training end events
 ---
 
-# _log_debug_samples
+## _log_debug_samples
 ---
-:::ultralytics.yolo.utils.callbacks.clearml._log_debug_samples
+### ::: ultralytics.yolo.utils.callbacks.clearml._log_debug_samples
 <br><br>
 
-# _log_plot
+## _log_plot
 ---
-:::ultralytics.yolo.utils.callbacks.clearml._log_plot
+### ::: ultralytics.yolo.utils.callbacks.clearml._log_plot
 <br><br>
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.clearml.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.clearml.on_pretrain_routine_start
 <br><br>
 
-# on_train_epoch_end
+## on_train_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.clearml.on_train_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.clearml.on_train_epoch_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.clearml.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.clearml.on_fit_epoch_end
 <br><br>
 
-# on_val_end
+## on_val_end
 ---
-:::ultralytics.yolo.utils.callbacks.clearml.on_val_end
+### ::: ultralytics.yolo.utils.callbacks.clearml.on_val_end
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.clearml.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.clearml.on_train_end
 <br><br>

docs/reference/yolo/utils/callbacks/comet.md

@@ -3,122 +3,122 @@ description: Learn about YOLO callbacks using the Comet.ml platform, enhancing o
 keywords: Ultralytics, YOLO, callbacks, Comet ML, log images, log predictions, log plots, fetch metadata, fetch annotations, create experiment data, format experiment data
 ---
 
-# _get_comet_mode
+## _get_comet_mode
 ---
-:::ultralytics.yolo.utils.callbacks.comet._get_comet_mode
+### ::: ultralytics.yolo.utils.callbacks.comet._get_comet_mode
 <br><br>
 
-# _get_comet_model_name
+## _get_comet_model_name
 ---
-:::ultralytics.yolo.utils.callbacks.comet._get_comet_model_name
+### ::: ultralytics.yolo.utils.callbacks.comet._get_comet_model_name
 <br><br>
 
-# _get_eval_batch_logging_interval
+## _get_eval_batch_logging_interval
 ---
-:::ultralytics.yolo.utils.callbacks.comet._get_eval_batch_logging_interval
+### ::: ultralytics.yolo.utils.callbacks.comet._get_eval_batch_logging_interval
 <br><br>
 
-# _get_max_image_predictions_to_log
+## _get_max_image_predictions_to_log
 ---
-:::ultralytics.yolo.utils.callbacks.comet._get_max_image_predictions_to_log
+### ::: ultralytics.yolo.utils.callbacks.comet._get_max_image_predictions_to_log
 <br><br>
 
-# _scale_confidence_score
+## _scale_confidence_score
 ---
-:::ultralytics.yolo.utils.callbacks.comet._scale_confidence_score
+### ::: ultralytics.yolo.utils.callbacks.comet._scale_confidence_score
 <br><br>
 
-# _should_log_confusion_matrix
+## _should_log_confusion_matrix
 ---
-:::ultralytics.yolo.utils.callbacks.comet._should_log_confusion_matrix
+### ::: ultralytics.yolo.utils.callbacks.comet._should_log_confusion_matrix
 <br><br>
 
-# _should_log_image_predictions
+## _should_log_image_predictions
 ---
-:::ultralytics.yolo.utils.callbacks.comet._should_log_image_predictions
+### ::: ultralytics.yolo.utils.callbacks.comet._should_log_image_predictions
 <br><br>
 
-# _get_experiment_type
+## _get_experiment_type
 ---
-:::ultralytics.yolo.utils.callbacks.comet._get_experiment_type
+### ::: ultralytics.yolo.utils.callbacks.comet._get_experiment_type
 <br><br>
 
-# _create_experiment
+## _create_experiment
 ---
-:::ultralytics.yolo.utils.callbacks.comet._create_experiment
+### ::: ultralytics.yolo.utils.callbacks.comet._create_experiment
 <br><br>
 
-# _fetch_trainer_metadata
+## _fetch_trainer_metadata
 ---
-:::ultralytics.yolo.utils.callbacks.comet._fetch_trainer_metadata
+### ::: ultralytics.yolo.utils.callbacks.comet._fetch_trainer_metadata
 <br><br>
 
-# _scale_bounding_box_to_original_image_shape
+## _scale_bounding_box_to_original_image_shape
 ---
-:::ultralytics.yolo.utils.callbacks.comet._scale_bounding_box_to_original_image_shape
+### ::: ultralytics.yolo.utils.callbacks.comet._scale_bounding_box_to_original_image_shape
 <br><br>
 
-# _format_ground_truth_annotations_for_detection
+## _format_ground_truth_annotations_for_detection
 ---
-:::ultralytics.yolo.utils.callbacks.comet._format_ground_truth_annotations_for_detection
+### ::: ultralytics.yolo.utils.callbacks.comet._format_ground_truth_annotations_for_detection
 <br><br>
 
-# _format_prediction_annotations_for_detection
+## _format_prediction_annotations_for_detection
 ---
-:::ultralytics.yolo.utils.callbacks.comet._format_prediction_annotations_for_detection
+### ::: ultralytics.yolo.utils.callbacks.comet._format_prediction_annotations_for_detection
 <br><br>
 
-# _fetch_annotations
+## _fetch_annotations
 ---
-:::ultralytics.yolo.utils.callbacks.comet._fetch_annotations
+### ::: ultralytics.yolo.utils.callbacks.comet._fetch_annotations
 <br><br>
 
-# _create_prediction_metadata_map
+## _create_prediction_metadata_map
 ---
-:::ultralytics.yolo.utils.callbacks.comet._create_prediction_metadata_map
+### ::: ultralytics.yolo.utils.callbacks.comet._create_prediction_metadata_map
 <br><br>
 
-# _log_confusion_matrix
+## _log_confusion_matrix
 ---
-:::ultralytics.yolo.utils.callbacks.comet._log_confusion_matrix
+### ::: ultralytics.yolo.utils.callbacks.comet._log_confusion_matrix
 <br><br>
 
-# _log_images
+## _log_images
 ---
-:::ultralytics.yolo.utils.callbacks.comet._log_images
+### ::: ultralytics.yolo.utils.callbacks.comet._log_images
 <br><br>
 
-# _log_image_predictions
+## _log_image_predictions
 ---
-:::ultralytics.yolo.utils.callbacks.comet._log_image_predictions
+### ::: ultralytics.yolo.utils.callbacks.comet._log_image_predictions
 <br><br>
 
-# _log_plots
+## _log_plots
 ---
-:::ultralytics.yolo.utils.callbacks.comet._log_plots
+### ::: ultralytics.yolo.utils.callbacks.comet._log_plots
 <br><br>
 
-# _log_model
+## _log_model
 ---
-:::ultralytics.yolo.utils.callbacks.comet._log_model
+### ::: ultralytics.yolo.utils.callbacks.comet._log_model
 <br><br>
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.comet.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.comet.on_pretrain_routine_start
 <br><br>
 
-# on_train_epoch_end
+## on_train_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.comet.on_train_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.comet.on_train_epoch_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.comet.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.comet.on_fit_epoch_end
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.comet.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.comet.on_train_end
 <br><br>

docs/reference/yolo/utils/callbacks/dvc.md

@@ -3,52 +3,52 @@ description: Explore Ultralytics YOLO Utils DVC Callbacks such as logging images
 keywords: Ultralytics, YOLO, Utils, DVC, Callbacks, images, plots, confusion matrices, training progress
 ---
 
-# _logger_disabled
+## _logger_disabled
 ---
-:::ultralytics.yolo.utils.callbacks.dvc._logger_disabled
+### ::: ultralytics.yolo.utils.callbacks.dvc._logger_disabled
 <br><br>
 
-# _log_images
+## _log_images
 ---
-:::ultralytics.yolo.utils.callbacks.dvc._log_images
+### ::: ultralytics.yolo.utils.callbacks.dvc._log_images
 <br><br>
 
-# _log_plots
+## _log_plots
 ---
-:::ultralytics.yolo.utils.callbacks.dvc._log_plots
+### ::: ultralytics.yolo.utils.callbacks.dvc._log_plots
 <br><br>
 
-# _log_confusion_matrix
+## _log_confusion_matrix
 ---
-:::ultralytics.yolo.utils.callbacks.dvc._log_confusion_matrix
+### ::: ultralytics.yolo.utils.callbacks.dvc._log_confusion_matrix
 <br><br>
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.dvc.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.dvc.on_pretrain_routine_start
 <br><br>
 
-# on_pretrain_routine_end
+## on_pretrain_routine_end
 ---
-:::ultralytics.yolo.utils.callbacks.dvc.on_pretrain_routine_end
+### ::: ultralytics.yolo.utils.callbacks.dvc.on_pretrain_routine_end
 <br><br>
 
-# on_train_start
+## on_train_start
 ---
-:::ultralytics.yolo.utils.callbacks.dvc.on_train_start
+### ::: ultralytics.yolo.utils.callbacks.dvc.on_train_start
 <br><br>
 
-# on_train_epoch_start
+## on_train_epoch_start
 ---
-:::ultralytics.yolo.utils.callbacks.dvc.on_train_epoch_start
+### ::: ultralytics.yolo.utils.callbacks.dvc.on_train_epoch_start
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.dvc.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.dvc.on_fit_epoch_end
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.dvc.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.dvc.on_train_end
 <br><br>

docs/reference/yolo/utils/callbacks/hub.md

@@ -3,42 +3,42 @@ description: Improve YOLOv5 model training with Ultralytics' on-train callbacks.
 keywords: Ultralytics, YOLO, callbacks, on_pretrain_routine_end, on_fit_epoch_end, on_train_start, on_val_start, on_predict_start, on_export_start
 ---
 
-# on_pretrain_routine_end
+## on_pretrain_routine_end
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_pretrain_routine_end
+### ::: ultralytics.yolo.utils.callbacks.hub.on_pretrain_routine_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.hub.on_fit_epoch_end
 <br><br>
 
-# on_model_save
+## on_model_save
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_model_save
+### ::: ultralytics.yolo.utils.callbacks.hub.on_model_save
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.hub.on_train_end
 <br><br>
 
-# on_train_start
+## on_train_start
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_train_start
+### ::: ultralytics.yolo.utils.callbacks.hub.on_train_start
 <br><br>
 
-# on_val_start
+## on_val_start
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_val_start
+### ::: ultralytics.yolo.utils.callbacks.hub.on_val_start
 <br><br>
 
-# on_predict_start
+## on_predict_start
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_predict_start
+### ::: ultralytics.yolo.utils.callbacks.hub.on_predict_start
 <br><br>
 
-# on_export_start
+## on_export_start
 ---
-:::ultralytics.yolo.utils.callbacks.hub.on_export_start
+### ::: ultralytics.yolo.utils.callbacks.hub.on_export_start
 <br><br>

docs/reference/yolo/utils/callbacks/mlflow.md

@@ -3,17 +3,17 @@ description: Track model performance and metrics with MLflow in YOLOv5. Use call
 keywords: Ultralytics, YOLO, Utils, MLflow, callbacks, on_pretrain_routine_end, on_train_end, Tracking, Model Management, training
 ---
 
-# on_pretrain_routine_end
+## on_pretrain_routine_end
 ---
-:::ultralytics.yolo.utils.callbacks.mlflow.on_pretrain_routine_end
+### ::: ultralytics.yolo.utils.callbacks.mlflow.on_pretrain_routine_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.mlflow.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.mlflow.on_fit_epoch_end
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.mlflow.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.mlflow.on_train_end
 <br><br>

docs/reference/yolo/utils/callbacks/neptune.md

@@ -3,42 +3,42 @@ description: Improve YOLOv5 training with Neptune, a powerful logging tool. Trac
 keywords: Ultralytics, YOLO, Neptune, Callbacks, log scalars, log images, log plots, training, validation
 ---
 
-# _log_scalars
+## _log_scalars
 ---
-:::ultralytics.yolo.utils.callbacks.neptune._log_scalars
+### ::: ultralytics.yolo.utils.callbacks.neptune._log_scalars
 <br><br>
 
-# _log_images
+## _log_images
 ---
-:::ultralytics.yolo.utils.callbacks.neptune._log_images
+### ::: ultralytics.yolo.utils.callbacks.neptune._log_images
 <br><br>
 
-# _log_plot
+## _log_plot
 ---
-:::ultralytics.yolo.utils.callbacks.neptune._log_plot
+### ::: ultralytics.yolo.utils.callbacks.neptune._log_plot
 <br><br>
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.neptune.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.neptune.on_pretrain_routine_start
 <br><br>
 
-# on_train_epoch_end
+## on_train_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.neptune.on_train_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.neptune.on_train_epoch_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.neptune.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.neptune.on_fit_epoch_end
 <br><br>
 
-# on_val_end
+## on_val_end
 ---
-:::ultralytics.yolo.utils.callbacks.neptune.on_val_end
+### ::: ultralytics.yolo.utils.callbacks.neptune.on_val_end
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.neptune.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.neptune.on_train_end
 <br><br>

docs/reference/yolo/utils/callbacks/raytune.md

@@ -3,7 +3,7 @@ description: '"Improve YOLO model performance with on_fit_epoch_end callback. Le
 keywords: on_fit_epoch_end, Ultralytics YOLO, callback function, training, model tuning
 ---
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.raytune.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.raytune.on_fit_epoch_end
 <br><br>

docs/reference/yolo/utils/callbacks/tensorboard.md

@@ -3,22 +3,22 @@ description: Learn how to monitor the training process with Tensorboard using Ul
 keywords: TensorBoard callbacks, YOLO training, ultralytics YOLO
 ---
 
-# _log_scalars
+## _log_scalars
 ---
-:::ultralytics.yolo.utils.callbacks.tensorboard._log_scalars
+### ::: ultralytics.yolo.utils.callbacks.tensorboard._log_scalars
 <br><br>
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.tensorboard.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.tensorboard.on_pretrain_routine_start
 <br><br>
 
-# on_batch_end
+## on_batch_end
 ---
-:::ultralytics.yolo.utils.callbacks.tensorboard.on_batch_end
+### ::: ultralytics.yolo.utils.callbacks.tensorboard.on_batch_end
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.tensorboard.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.tensorboard.on_fit_epoch_end
 <br><br>

docs/reference/yolo/utils/callbacks/wb.md

@@ -3,27 +3,27 @@ description: Learn how to use Ultralytics YOLO's built-in callbacks `on_pretrain
 keywords: Ultralytics, YOLO, callbacks, weights, biases, training
 ---
 
-# _log_plots
+## _log_plots
 ---
-:::ultralytics.yolo.utils.callbacks.wb._log_plots
+### ::: ultralytics.yolo.utils.callbacks.wb._log_plots
 <br><br>
 
-# on_pretrain_routine_start
+## on_pretrain_routine_start
 ---
-:::ultralytics.yolo.utils.callbacks.wb.on_pretrain_routine_start
+### ::: ultralytics.yolo.utils.callbacks.wb.on_pretrain_routine_start
 <br><br>
 
-# on_fit_epoch_end
+## on_fit_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.wb.on_fit_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.wb.on_fit_epoch_end
 <br><br>
 
-# on_train_epoch_end
+## on_train_epoch_end
 ---
-:::ultralytics.yolo.utils.callbacks.wb.on_train_epoch_end
+### ::: ultralytics.yolo.utils.callbacks.wb.on_train_epoch_end
 <br><br>
 
-# on_train_end
+## on_train_end
 ---
-:::ultralytics.yolo.utils.callbacks.wb.on_train_end
+### ::: ultralytics.yolo.utils.callbacks.wb.on_train_end
 <br><br>

docs/reference/yolo/utils/checks.md

@@ -3,87 +3,87 @@ description: 'Check functions for YOLO utils: image size, version, font, require
 keywords: YOLO, Ultralytics, Utils, Checks, image sizing, version updates, font compatibility, Python requirements, file suffixes, YAML syntax, image showing, AMP
 ---
 
-# is_ascii
+## is_ascii
 ---
-:::ultralytics.yolo.utils.checks.is_ascii
+### ::: ultralytics.yolo.utils.checks.is_ascii
 <br><br>
 
-# check_imgsz
+## check_imgsz
 ---
-:::ultralytics.yolo.utils.checks.check_imgsz
+### ::: ultralytics.yolo.utils.checks.check_imgsz
 <br><br>
 
-# check_version
+## check_version
 ---
-:::ultralytics.yolo.utils.checks.check_version
+### ::: ultralytics.yolo.utils.checks.check_version
 <br><br>
 
-# check_latest_pypi_version
+## check_latest_pypi_version
 ---
-:::ultralytics.yolo.utils.checks.check_latest_pypi_version
+### ::: ultralytics.yolo.utils.checks.check_latest_pypi_version
 <br><br>
 
-# check_pip_update_available
+## check_pip_update_available
 ---
-:::ultralytics.yolo.utils.checks.check_pip_update_available
+### ::: ultralytics.yolo.utils.checks.check_pip_update_available
 <br><br>
 
-# check_font
+## check_font
 ---
-:::ultralytics.yolo.utils.checks.check_font
+### ::: ultralytics.yolo.utils.checks.check_font
 <br><br>
 
-# check_python
+## check_python
 ---
-:::ultralytics.yolo.utils.checks.check_python
+### ::: ultralytics.yolo.utils.checks.check_python
 <br><br>
 
-# check_requirements
+## check_requirements
 ---
-:::ultralytics.yolo.utils.checks.check_requirements
+### ::: ultralytics.yolo.utils.checks.check_requirements
 <br><br>
 
-# check_suffix
+## check_suffix
 ---
-:::ultralytics.yolo.utils.checks.check_suffix
+### ::: ultralytics.yolo.utils.checks.check_suffix
 <br><br>
 
-# check_yolov5u_filename
+## check_yolov5u_filename
 ---
-:::ultralytics.yolo.utils.checks.check_yolov5u_filename
+### ::: ultralytics.yolo.utils.checks.check_yolov5u_filename
 <br><br>
 
-# check_file
+## check_file
 ---
-:::ultralytics.yolo.utils.checks.check_file
+### ::: ultralytics.yolo.utils.checks.check_file
 <br><br>
 
-# check_yaml
+## check_yaml
 ---
-:::ultralytics.yolo.utils.checks.check_yaml
+### ::: ultralytics.yolo.utils.checks.check_yaml
 <br><br>
 
-# check_imshow
+## check_imshow
 ---
-:::ultralytics.yolo.utils.checks.check_imshow
+### ::: ultralytics.yolo.utils.checks.check_imshow
 <br><br>
 
-# check_yolo
+## check_yolo
 ---
-:::ultralytics.yolo.utils.checks.check_yolo
+### ::: ultralytics.yolo.utils.checks.check_yolo
 <br><br>
 
-# check_amp
+## check_amp
 ---
-:::ultralytics.yolo.utils.checks.check_amp
+### ::: ultralytics.yolo.utils.checks.check_amp
 <br><br>
 
-# git_describe
+## git_describe
 ---
-:::ultralytics.yolo.utils.checks.git_describe
+### ::: ultralytics.yolo.utils.checks.git_describe
 <br><br>
 
-# print_args
+## print_args
 ---
-:::ultralytics.yolo.utils.checks.print_args
+### ::: ultralytics.yolo.utils.checks.print_args
 <br><br>

docs/reference/yolo/utils/dist.md

@@ -3,22 +3,22 @@ description: Learn how to find free network port and generate DDP (Distributed D
 keywords: ultralytics, YOLO, utils, dist, distributed deep learning, DDP file, DDP cleanup
 ---
 
-# find_free_network_port
+## find_free_network_port
 ---
-:::ultralytics.yolo.utils.dist.find_free_network_port
+### ::: ultralytics.yolo.utils.dist.find_free_network_port
 <br><br>
 
-# generate_ddp_file
+## generate_ddp_file
 ---
-:::ultralytics.yolo.utils.dist.generate_ddp_file
+### ::: ultralytics.yolo.utils.dist.generate_ddp_file
 <br><br>
 
-# generate_ddp_command
+## generate_ddp_command
 ---
-:::ultralytics.yolo.utils.dist.generate_ddp_command
+### ::: ultralytics.yolo.utils.dist.generate_ddp_command
 <br><br>
 
-# ddp_cleanup
+## ddp_cleanup
 ---
-:::ultralytics.yolo.utils.dist.ddp_cleanup
+### ::: ultralytics.yolo.utils.dist.ddp_cleanup
 <br><br>

docs/reference/yolo/utils/downloads.md

@@ -3,32 +3,32 @@ description: Download and unzip YOLO pretrained models. Ultralytics YOLO docs ut
 keywords: Ultralytics YOLO, downloads, trained models, datasets, weights, deep learning, computer vision
 ---
 
-# is_url
+## is_url
 ---
-:::ultralytics.yolo.utils.downloads.is_url
+### ::: ultralytics.yolo.utils.downloads.is_url
 <br><br>
 
-# unzip_file
+## unzip_file
 ---
-:::ultralytics.yolo.utils.downloads.unzip_file
+### ::: ultralytics.yolo.utils.downloads.unzip_file
 <br><br>
 
-# check_disk_space
+## check_disk_space
 ---
-:::ultralytics.yolo.utils.downloads.check_disk_space
+### ::: ultralytics.yolo.utils.downloads.check_disk_space
 <br><br>
 
-# safe_download
+## safe_download
 ---
-:::ultralytics.yolo.utils.downloads.safe_download
+### ::: ultralytics.yolo.utils.downloads.safe_download
 <br><br>
 
-# attempt_download_asset
+## attempt_download_asset
 ---
-:::ultralytics.yolo.utils.downloads.attempt_download_asset
+### ::: ultralytics.yolo.utils.downloads.attempt_download_asset
 <br><br>
 
-# download
+## download
 ---
-:::ultralytics.yolo.utils.downloads.download
+### ::: ultralytics.yolo.utils.downloads.download
 <br><br>

docs/reference/yolo/utils/errors.md

@@ -3,7 +3,7 @@ description: Learn about HUBModelError in Ultralytics YOLO Docs. Resolve the err
 keywords: HUBModelError, Ultralytics YOLO, YOLO Documentation, Object detection errors, YOLO Errors, HUBModelError Solutions
 ---
 
-# HUBModelError
+## HUBModelError
 ---
-:::ultralytics.yolo.utils.errors.HUBModelError
+### ::: ultralytics.yolo.utils.errors.HUBModelError
 <br><br>

docs/reference/yolo/utils/files.md

@@ -3,37 +3,37 @@ description: 'Learn about Ultralytics YOLO files and directory utilities: Workin
 keywords: YOLO, object detection, file utils, file age, file size, working directory, make directories, Ultralytics Docs
 ---
 
-# WorkingDirectory
+## WorkingDirectory
 ---
-:::ultralytics.yolo.utils.files.WorkingDirectory
+### ::: ultralytics.yolo.utils.files.WorkingDirectory
 <br><br>
 
-# increment_path
+## increment_path
 ---
-:::ultralytics.yolo.utils.files.increment_path
+### ::: ultralytics.yolo.utils.files.increment_path
 <br><br>
 
-# file_age
+## file_age
 ---
-:::ultralytics.yolo.utils.files.file_age
+### ::: ultralytics.yolo.utils.files.file_age
 <br><br>
 
-# file_date
+## file_date
 ---
-:::ultralytics.yolo.utils.files.file_date
+### ::: ultralytics.yolo.utils.files.file_date
 <br><br>
 
-# file_size
+## file_size
 ---
-:::ultralytics.yolo.utils.files.file_size
+### ::: ultralytics.yolo.utils.files.file_size
 <br><br>
 
-# get_latest_run
+## get_latest_run
 ---
-:::ultralytics.yolo.utils.files.get_latest_run
+### ::: ultralytics.yolo.utils.files.get_latest_run
 <br><br>
 
-# make_dirs
+## make_dirs
 ---
-:::ultralytics.yolo.utils.files.make_dirs
+### ::: ultralytics.yolo.utils.files.make_dirs
 <br><br>

docs/reference/yolo/utils/instance.md

@@ -3,17 +3,17 @@ description: Learn about Bounding Boxes (Bboxes) and _ntuple in Ultralytics YOLO
 keywords: Ultralytics, YOLO, Bboxes, _ntuple, object detection, instance segmentation
 ---
 
-# Bboxes
+## Bboxes
 ---
-:::ultralytics.yolo.utils.instance.Bboxes
+### ::: ultralytics.yolo.utils.instance.Bboxes
 <br><br>
 
-# Instances
+## Instances
 ---
-:::ultralytics.yolo.utils.instance.Instances
+### ::: ultralytics.yolo.utils.instance.Instances
 <br><br>
 
-# _ntuple
+## _ntuple
 ---
-:::ultralytics.yolo.utils.instance._ntuple
+### ::: ultralytics.yolo.utils.instance._ntuple
 <br><br>

docs/reference/yolo/utils/loss.md

@@ -3,42 +3,42 @@ description: Learn about Varifocal Loss and Keypoint Loss in Ultralytics YOLO fo
 keywords: Ultralytics, YOLO, loss functions, object detection, keypoint detection, segmentation, classification
 ---
 
-# VarifocalLoss
+## VarifocalLoss
 ---
-:::ultralytics.yolo.utils.loss.VarifocalLoss
+### ::: ultralytics.yolo.utils.loss.VarifocalLoss
 <br><br>
 
-# FocalLoss
+## FocalLoss
 ---
-:::ultralytics.yolo.utils.loss.FocalLoss
+### ::: ultralytics.yolo.utils.loss.FocalLoss
 <br><br>
 
-# BboxLoss
+## BboxLoss
 ---
-:::ultralytics.yolo.utils.loss.BboxLoss
+### ::: ultralytics.yolo.utils.loss.BboxLoss
 <br><br>
 
-# KeypointLoss
+## KeypointLoss
 ---
-:::ultralytics.yolo.utils.loss.KeypointLoss
+### ::: ultralytics.yolo.utils.loss.KeypointLoss
 <br><br>
 
-# v8DetectionLoss
+## v8DetectionLoss
 ---
-:::ultralytics.yolo.utils.loss.v8DetectionLoss
+### ::: ultralytics.yolo.utils.loss.v8DetectionLoss
 <br><br>
 
-# v8SegmentationLoss
+## v8SegmentationLoss
 ---
-:::ultralytics.yolo.utils.loss.v8SegmentationLoss
+### ::: ultralytics.yolo.utils.loss.v8SegmentationLoss
 <br><br>
 
-# v8PoseLoss
+## v8PoseLoss
 ---
-:::ultralytics.yolo.utils.loss.v8PoseLoss
+### ::: ultralytics.yolo.utils.loss.v8PoseLoss
 <br><br>
 
-# v8ClassificationLoss
+## v8ClassificationLoss
 ---
-:::ultralytics.yolo.utils.loss.v8ClassificationLoss
+### ::: ultralytics.yolo.utils.loss.v8ClassificationLoss
 <br><br>

docs/reference/yolo/utils/metrics.md

@@ -3,92 +3,92 @@ description: Explore Ultralytics YOLO's FocalLoss, DetMetrics, PoseMetrics, Clas
 keywords: YOLOv5, metrics, losses, confusion matrix, detection metrics, pose metrics, classification metrics, intersection over area, intersection over union, keypoint intersection over union, average precision, per class average precision, Ultralytics Docs
 ---
 
-# ConfusionMatrix
+## ConfusionMatrix
 ---
-:::ultralytics.yolo.utils.metrics.ConfusionMatrix
+### ::: ultralytics.yolo.utils.metrics.ConfusionMatrix
 <br><br>
 
-# Metric
+## Metric
 ---
-:::ultralytics.yolo.utils.metrics.Metric
+### ::: ultralytics.yolo.utils.metrics.Metric
 <br><br>
 
-# DetMetrics
+## DetMetrics
 ---
-:::ultralytics.yolo.utils.metrics.DetMetrics
+### ::: ultralytics.yolo.utils.metrics.DetMetrics
 <br><br>
 
-# SegmentMetrics
+## SegmentMetrics
 ---
-:::ultralytics.yolo.utils.metrics.SegmentMetrics
+### ::: ultralytics.yolo.utils.metrics.SegmentMetrics
 <br><br>
 
-# PoseMetrics
+## PoseMetrics
 ---
-:::ultralytics.yolo.utils.metrics.PoseMetrics
+### ::: ultralytics.yolo.utils.metrics.PoseMetrics
 <br><br>
 
-# ClassifyMetrics
+## ClassifyMetrics
 ---
-:::ultralytics.yolo.utils.metrics.ClassifyMetrics
+### ::: ultralytics.yolo.utils.metrics.ClassifyMetrics
 <br><br>
 
-# box_area
+## box_area
 ---
-:::ultralytics.yolo.utils.metrics.box_area
+### ::: ultralytics.yolo.utils.metrics.box_area
 <br><br>
 
-# bbox_ioa
+## bbox_ioa
 ---
-:::ultralytics.yolo.utils.metrics.bbox_ioa
+### ::: ultralytics.yolo.utils.metrics.bbox_ioa
 <br><br>
 
-# box_iou
+## box_iou
 ---
-:::ultralytics.yolo.utils.metrics.box_iou
+### ::: ultralytics.yolo.utils.metrics.box_iou
 <br><br>
 
-# bbox_iou
+## bbox_iou
 ---
-:::ultralytics.yolo.utils.metrics.bbox_iou
+### ::: ultralytics.yolo.utils.metrics.bbox_iou
 <br><br>
 
-# mask_iou
+## mask_iou
 ---
-:::ultralytics.yolo.utils.metrics.mask_iou
+### ::: ultralytics.yolo.utils.metrics.mask_iou
 <br><br>
 
-# kpt_iou
+## kpt_iou
 ---
-:::ultralytics.yolo.utils.metrics.kpt_iou
+### ::: ultralytics.yolo.utils.metrics.kpt_iou
 <br><br>
 
-# smooth_BCE
+## smooth_BCE
 ---
-:::ultralytics.yolo.utils.metrics.smooth_BCE
+### ::: ultralytics.yolo.utils.metrics.smooth_BCE
 <br><br>
 
-# smooth
+## smooth
 ---
-:::ultralytics.yolo.utils.metrics.smooth
+### ::: ultralytics.yolo.utils.metrics.smooth
 <br><br>
 
-# plot_pr_curve
+## plot_pr_curve
 ---
-:::ultralytics.yolo.utils.metrics.plot_pr_curve
+### ::: ultralytics.yolo.utils.metrics.plot_pr_curve
 <br><br>
 
-# plot_mc_curve
+## plot_mc_curve
 ---
-:::ultralytics.yolo.utils.metrics.plot_mc_curve
+### ::: ultralytics.yolo.utils.metrics.plot_mc_curve
 <br><br>
 
-# compute_ap
+## compute_ap
 ---
-:::ultralytics.yolo.utils.metrics.compute_ap
+### ::: ultralytics.yolo.utils.metrics.compute_ap
 <br><br>
 
-# ap_per_class
+## ap_per_class
 ---
-:::ultralytics.yolo.utils.metrics.ap_per_class
+### ::: ultralytics.yolo.utils.metrics.ap_per_class
 <br><br>

docs/reference/yolo/utils/ops.md

@@ -3,137 +3,137 @@ description: Learn about various utility functions in Ultralytics YOLO, includin
 keywords: Ultralytics, YOLO, Utils Ops, Functions, coco80_to_coco91_class, scale_boxes, non_max_suppression, clip_coords, xyxy2xywh, xywhn2xyxy, xyn2xy, xyxy2ltwh, ltwh2xyxy, resample_segments, process_mask_upsample, process_mask_native, masks2segments, clean_str
 ---
 
-# Profile
+## Profile
 ---
-:::ultralytics.yolo.utils.ops.Profile
+### ::: ultralytics.yolo.utils.ops.Profile
 <br><br>
 
-# coco80_to_coco91_class
+## coco80_to_coco91_class
 ---
-:::ultralytics.yolo.utils.ops.coco80_to_coco91_class
+### ::: ultralytics.yolo.utils.ops.coco80_to_coco91_class
 <br><br>
 
-# segment2box
+## segment2box
 ---
-:::ultralytics.yolo.utils.ops.segment2box
+### ::: ultralytics.yolo.utils.ops.segment2box
 <br><br>
 
-# scale_boxes
+## scale_boxes
 ---
-:::ultralytics.yolo.utils.ops.scale_boxes
+### ::: ultralytics.yolo.utils.ops.scale_boxes
 <br><br>
 
-# make_divisible
+## make_divisible
 ---
-:::ultralytics.yolo.utils.ops.make_divisible
+### ::: ultralytics.yolo.utils.ops.make_divisible
 <br><br>
 
-# non_max_suppression
+## non_max_suppression
 ---
-:::ultralytics.yolo.utils.ops.non_max_suppression
+### ::: ultralytics.yolo.utils.ops.non_max_suppression
 <br><br>
 
-# clip_boxes
+## clip_boxes
 ---
-:::ultralytics.yolo.utils.ops.clip_boxes
+### ::: ultralytics.yolo.utils.ops.clip_boxes
 <br><br>
 
-# clip_coords
+## clip_coords
 ---
-:::ultralytics.yolo.utils.ops.clip_coords
+### ::: ultralytics.yolo.utils.ops.clip_coords
 <br><br>
 
-# scale_image
+## scale_image
 ---
-:::ultralytics.yolo.utils.ops.scale_image
+### ::: ultralytics.yolo.utils.ops.scale_image
 <br><br>
 
-# xyxy2xywh
+## xyxy2xywh
 ---
-:::ultralytics.yolo.utils.ops.xyxy2xywh
+### ::: ultralytics.yolo.utils.ops.xyxy2xywh
 <br><br>
 
-# xywh2xyxy
+## xywh2xyxy
 ---
-:::ultralytics.yolo.utils.ops.xywh2xyxy
+### ::: ultralytics.yolo.utils.ops.xywh2xyxy
 <br><br>
 
-# xywhn2xyxy
+## xywhn2xyxy
 ---
-:::ultralytics.yolo.utils.ops.xywhn2xyxy
+### ::: ultralytics.yolo.utils.ops.xywhn2xyxy
 <br><br>
 
-# xyxy2xywhn
+## xyxy2xywhn
 ---
-:::ultralytics.yolo.utils.ops.xyxy2xywhn
+### ::: ultralytics.yolo.utils.ops.xyxy2xywhn
 <br><br>
 
-# xyn2xy
+## xyn2xy
 ---
-:::ultralytics.yolo.utils.ops.xyn2xy
+### ::: ultralytics.yolo.utils.ops.xyn2xy
 <br><br>
 
-# xywh2ltwh
+## xywh2ltwh
 ---
-:::ultralytics.yolo.utils.ops.xywh2ltwh
+### ::: ultralytics.yolo.utils.ops.xywh2ltwh
 <br><br>
 
-# xyxy2ltwh
+## xyxy2ltwh
 ---
-:::ultralytics.yolo.utils.ops.xyxy2ltwh
+### ::: ultralytics.yolo.utils.ops.xyxy2ltwh
 <br><br>
 
-# ltwh2xywh
+## ltwh2xywh
 ---
-:::ultralytics.yolo.utils.ops.ltwh2xywh
+### ::: ultralytics.yolo.utils.ops.ltwh2xywh
 <br><br>
 
-# ltwh2xyxy
+## ltwh2xyxy
 ---
-:::ultralytics.yolo.utils.ops.ltwh2xyxy
+### ::: ultralytics.yolo.utils.ops.ltwh2xyxy
 <br><br>
 
-# segments2boxes
+## segments2boxes
 ---
-:::ultralytics.yolo.utils.ops.segments2boxes
+### ::: ultralytics.yolo.utils.ops.segments2boxes
 <br><br>
 
-# resample_segments
+## resample_segments
 ---
-:::ultralytics.yolo.utils.ops.resample_segments
+### ::: ultralytics.yolo.utils.ops.resample_segments
 <br><br>
 
-# crop_mask
+## crop_mask
 ---
-:::ultralytics.yolo.utils.ops.crop_mask
+### ::: ultralytics.yolo.utils.ops.crop_mask
 <br><br>
 
-# process_mask_upsample
+## process_mask_upsample
 ---
-:::ultralytics.yolo.utils.ops.process_mask_upsample
+### ::: ultralytics.yolo.utils.ops.process_mask_upsample
 <br><br>
 
-# process_mask
+## process_mask
 ---
-:::ultralytics.yolo.utils.ops.process_mask
+### ::: ultralytics.yolo.utils.ops.process_mask
 <br><br>
 
-# process_mask_native
+## process_mask_native
 ---
-:::ultralytics.yolo.utils.ops.process_mask_native
+### ::: ultralytics.yolo.utils.ops.process_mask_native
 <br><br>
 
-# scale_coords
+## scale_coords
 ---
-:::ultralytics.yolo.utils.ops.scale_coords
+### ::: ultralytics.yolo.utils.ops.scale_coords
 <br><br>
 
-# masks2segments
+## masks2segments
 ---
-:::ultralytics.yolo.utils.ops.masks2segments
+### ::: ultralytics.yolo.utils.ops.masks2segments
 <br><br>
 
-# clean_str
+## clean_str
 ---
-:::ultralytics.yolo.utils.ops.clean_str
+### ::: ultralytics.yolo.utils.ops.clean_str
 <br><br>

docs/reference/yolo/utils/patches.md

@@ -3,22 +3,22 @@ description: Learn how to use the Ultralytics YOLO Utils package's imread and im
 keywords: imread, imshow, ultralytics, YOLO, image files, torchsave
 ---
 
-# imread
+## imread
 ---
-:::ultralytics.yolo.utils.patches.imread
+### ::: ultralytics.yolo.utils.patches.imread
 <br><br>
 
-# imwrite
+## imwrite
 ---
-:::ultralytics.yolo.utils.patches.imwrite
+### ::: ultralytics.yolo.utils.patches.imwrite
 <br><br>
 
-# imshow
+## imshow
 ---
-:::ultralytics.yolo.utils.patches.imshow
+### ::: ultralytics.yolo.utils.patches.imshow
 <br><br>
 
-# torch_save
+## torch_save
 ---
-:::ultralytics.yolo.utils.patches.torch_save
+### ::: ultralytics.yolo.utils.patches.torch_save
 <br><br>

docs/reference/yolo/utils/plotting.md

@@ -3,42 +3,42 @@ description: 'Discover the power of YOLO''s plotting functions: Colors, Labels a
 keywords: YOLO, object detection, plotting, visualization, annotator, save one box, plot results, feature visualization, Ultralytics
 ---
 
-# Colors
+## Colors
 ---
-:::ultralytics.yolo.utils.plotting.Colors
+### ::: ultralytics.yolo.utils.plotting.Colors
 <br><br>
 
-# Annotator
+## Annotator
 ---
-:::ultralytics.yolo.utils.plotting.Annotator
+### ::: ultralytics.yolo.utils.plotting.Annotator
 <br><br>
 
-# plot_labels
+## plot_labels
 ---
-:::ultralytics.yolo.utils.plotting.plot_labels
+### ::: ultralytics.yolo.utils.plotting.plot_labels
 <br><br>
 
-# save_one_box
+## save_one_box
 ---
-:::ultralytics.yolo.utils.plotting.save_one_box
+### ::: ultralytics.yolo.utils.plotting.save_one_box
 <br><br>
 
-# plot_images
+## plot_images
 ---
-:::ultralytics.yolo.utils.plotting.plot_images
+### ::: ultralytics.yolo.utils.plotting.plot_images
 <br><br>
 
-# plot_results
+## plot_results
 ---
-:::ultralytics.yolo.utils.plotting.plot_results
+### ::: ultralytics.yolo.utils.plotting.plot_results
 <br><br>
 
-# output_to_target
+## output_to_target
 ---
-:::ultralytics.yolo.utils.plotting.output_to_target
+### ::: ultralytics.yolo.utils.plotting.output_to_target
 <br><br>
 
-# feature_visualization
+## feature_visualization
 ---
-:::ultralytics.yolo.utils.plotting.feature_visualization
+### ::: ultralytics.yolo.utils.plotting.feature_visualization
 <br><br>

docs/reference/yolo/utils/tal.md

@@ -3,32 +3,32 @@ description: Improve your YOLO models with Ultralytics' TaskAlignedAssigner, sel
 keywords: Ultrayltics, YOLO, select_candidates_in_gts, make_anchor, bbox2dist, object detection, tracking
 ---
 
-# TaskAlignedAssigner
+## TaskAlignedAssigner
 ---
-:::ultralytics.yolo.utils.tal.TaskAlignedAssigner
+### ::: ultralytics.yolo.utils.tal.TaskAlignedAssigner
 <br><br>
 
-# select_candidates_in_gts
+## select_candidates_in_gts
 ---
-:::ultralytics.yolo.utils.tal.select_candidates_in_gts
+### ::: ultralytics.yolo.utils.tal.select_candidates_in_gts
 <br><br>
 
-# select_highest_overlaps
+## select_highest_overlaps
 ---
-:::ultralytics.yolo.utils.tal.select_highest_overlaps
+### ::: ultralytics.yolo.utils.tal.select_highest_overlaps
 <br><br>
 
-# make_anchors
+## make_anchors
 ---
-:::ultralytics.yolo.utils.tal.make_anchors
+### ::: ultralytics.yolo.utils.tal.make_anchors
 <br><br>
 
-# dist2bbox
+## dist2bbox
 ---
-:::ultralytics.yolo.utils.tal.dist2bbox
+### ::: ultralytics.yolo.utils.tal.dist2bbox
 <br><br>
 
-# bbox2dist
+## bbox2dist
 ---
-:::ultralytics.yolo.utils.tal.bbox2dist
+### ::: ultralytics.yolo.utils.tal.bbox2dist
 <br><br>

docs/reference/yolo/utils/torch_utils.md

@@ -3,132 +3,132 @@ description: Optimize your PyTorch models with Ultralytics YOLO's torch_utils fu
 keywords: Ultralytics YOLO, Torch, Utils, Pytorch, Object Detection
 ---
 
-# ModelEMA
+## ModelEMA
 ---
-:::ultralytics.yolo.utils.torch_utils.ModelEMA
+### ::: ultralytics.yolo.utils.torch_utils.ModelEMA
 <br><br>
 
-# EarlyStopping
+## EarlyStopping
 ---
-:::ultralytics.yolo.utils.torch_utils.EarlyStopping
+### ::: ultralytics.yolo.utils.torch_utils.EarlyStopping
 <br><br>
 
-# torch_distributed_zero_first
+## torch_distributed_zero_first
 ---
-:::ultralytics.yolo.utils.torch_utils.torch_distributed_zero_first
+### ::: ultralytics.yolo.utils.torch_utils.torch_distributed_zero_first
 <br><br>
 
-# smart_inference_mode
+## smart_inference_mode
 ---
-:::ultralytics.yolo.utils.torch_utils.smart_inference_mode
+### ::: ultralytics.yolo.utils.torch_utils.smart_inference_mode
 <br><br>
 
-# select_device
+## select_device
 ---
-:::ultralytics.yolo.utils.torch_utils.select_device
+### ::: ultralytics.yolo.utils.torch_utils.select_device
 <br><br>
 
-# time_sync
+## time_sync
 ---
-:::ultralytics.yolo.utils.torch_utils.time_sync
+### ::: ultralytics.yolo.utils.torch_utils.time_sync
 <br><br>
 
-# fuse_conv_and_bn
+## fuse_conv_and_bn
 ---
-:::ultralytics.yolo.utils.torch_utils.fuse_conv_and_bn
+### ::: ultralytics.yolo.utils.torch_utils.fuse_conv_and_bn
 <br><br>
 
-# fuse_deconv_and_bn
+## fuse_deconv_and_bn
 ---
-:::ultralytics.yolo.utils.torch_utils.fuse_deconv_and_bn
+### ::: ultralytics.yolo.utils.torch_utils.fuse_deconv_and_bn
 <br><br>
 
-# model_info
+## model_info
 ---
-:::ultralytics.yolo.utils.torch_utils.model_info
+### ::: ultralytics.yolo.utils.torch_utils.model_info
 <br><br>
 
-# get_num_params
+## get_num_params
 ---
-:::ultralytics.yolo.utils.torch_utils.get_num_params
+### ::: ultralytics.yolo.utils.torch_utils.get_num_params
 <br><br>
 
-# get_num_gradients
+## get_num_gradients
 ---
-:::ultralytics.yolo.utils.torch_utils.get_num_gradients
+### ::: ultralytics.yolo.utils.torch_utils.get_num_gradients
 <br><br>
 
-# model_info_for_loggers
+## model_info_for_loggers
 ---
-:::ultralytics.yolo.utils.torch_utils.model_info_for_loggers
+### ::: ultralytics.yolo.utils.torch_utils.model_info_for_loggers
 <br><br>
 
-# get_flops
+## get_flops
 ---
-:::ultralytics.yolo.utils.torch_utils.get_flops
+### ::: ultralytics.yolo.utils.torch_utils.get_flops
 <br><br>
 
-# get_flops_with_torch_profiler
+## get_flops_with_torch_profiler
 ---
-:::ultralytics.yolo.utils.torch_utils.get_flops_with_torch_profiler
+### ::: ultralytics.yolo.utils.torch_utils.get_flops_with_torch_profiler
 <br><br>
 
-# initialize_weights
+## initialize_weights
 ---
-:::ultralytics.yolo.utils.torch_utils.initialize_weights
+### ::: ultralytics.yolo.utils.torch_utils.initialize_weights
 <br><br>
 
-# scale_img
+## scale_img
 ---
-:::ultralytics.yolo.utils.torch_utils.scale_img
+### ::: ultralytics.yolo.utils.torch_utils.scale_img
 <br><br>
 
-# make_divisible
+## make_divisible
 ---
-:::ultralytics.yolo.utils.torch_utils.make_divisible
+### ::: ultralytics.yolo.utils.torch_utils.make_divisible
 <br><br>
 
-# copy_attr
+## copy_attr
 ---
-:::ultralytics.yolo.utils.torch_utils.copy_attr
+### ::: ultralytics.yolo.utils.torch_utils.copy_attr
 <br><br>
 
-# get_latest_opset
+## get_latest_opset
 ---
-:::ultralytics.yolo.utils.torch_utils.get_latest_opset
+### ::: ultralytics.yolo.utils.torch_utils.get_latest_opset
 <br><br>
 
-# intersect_dicts
+## intersect_dicts
 ---
-:::ultralytics.yolo.utils.torch_utils.intersect_dicts
+### ::: ultralytics.yolo.utils.torch_utils.intersect_dicts
 <br><br>
 
-# is_parallel
+## is_parallel
 ---
-:::ultralytics.yolo.utils.torch_utils.is_parallel
+### ::: ultralytics.yolo.utils.torch_utils.is_parallel
 <br><br>
 
-# de_parallel
+## de_parallel
 ---
-:::ultralytics.yolo.utils.torch_utils.de_parallel
+### ::: ultralytics.yolo.utils.torch_utils.de_parallel
 <br><br>
 
-# one_cycle
+## one_cycle
 ---
-:::ultralytics.yolo.utils.torch_utils.one_cycle
+### ::: ultralytics.yolo.utils.torch_utils.one_cycle
 <br><br>
 
-# init_seeds
+## init_seeds
 ---
-:::ultralytics.yolo.utils.torch_utils.init_seeds
+### ::: ultralytics.yolo.utils.torch_utils.init_seeds
 <br><br>
 
-# strip_optimizer
+## strip_optimizer
 ---
-:::ultralytics.yolo.utils.torch_utils.strip_optimizer
+### ::: ultralytics.yolo.utils.torch_utils.strip_optimizer
 <br><br>
 
-# profile
+## profile
 ---
-:::ultralytics.yolo.utils.torch_utils.profile
+### ::: ultralytics.yolo.utils.torch_utils.profile
 <br><br>

docs/reference/yolo/v8/classify/predict.md

@@ -3,12 +3,12 @@ description: Learn how to use ClassificationPredictor in Ultralytics YOLOv8 for
 keywords: Ultralytics, YOLO, v8, Classify Predictor, object detection, classification, computer vision
 ---
 
-# ClassificationPredictor
+## ClassificationPredictor
 ---
-:::ultralytics.yolo.v8.classify.predict.ClassificationPredictor
+### ::: ultralytics.yolo.v8.classify.predict.ClassificationPredictor
 <br><br>
 
-# predict
+## predict
 ---
-:::ultralytics.yolo.v8.classify.predict.predict
+### ::: ultralytics.yolo.v8.classify.predict.predict
 <br><br>

docs/reference/yolo/v8/classify/train.md

@@ -3,12 +3,12 @@ description: Train a custom image classification model using Ultralytics YOLOv8
 keywords: Ultralytics, YOLOv8, object detection, classification, training, API
 ---
 
-# ClassificationTrainer
+## ClassificationTrainer
 ---
-:::ultralytics.yolo.v8.classify.train.ClassificationTrainer
+### ::: ultralytics.yolo.v8.classify.train.ClassificationTrainer
 <br><br>
 
-# train
+## train
 ---
-:::ultralytics.yolo.v8.classify.train.train
+### ::: ultralytics.yolo.v8.classify.train.train
 <br><br>

docs/reference/yolo/v8/classify/val.md

@@ -3,12 +3,12 @@ description: Ensure model classification accuracy with Ultralytics YOLO's Classi
 keywords: ClassificationValidator, Ultralytics YOLO, Validation, Data Science, Deep Learning
 ---
 
-# ClassificationValidator
+## ClassificationValidator
 ---
-:::ultralytics.yolo.v8.classify.val.ClassificationValidator
+### ::: ultralytics.yolo.v8.classify.val.ClassificationValidator
 <br><br>
 
-# val
+## val
 ---
-:::ultralytics.yolo.v8.classify.val.val
+### ::: ultralytics.yolo.v8.classify.val.val
 <br><br>

docs/reference/yolo/v8/detect/predict.md

@@ -3,12 +3,12 @@ description: Detect and predict objects in images and videos using the Ultralyti
 keywords: detectionpredictor, ultralytics yolo, object detection, neural network, machine learning
 ---
 
-# DetectionPredictor
+## DetectionPredictor
 ---
-:::ultralytics.yolo.v8.detect.predict.DetectionPredictor
+### ::: ultralytics.yolo.v8.detect.predict.DetectionPredictor
 <br><br>
 
-# predict
+## predict
 ---
-:::ultralytics.yolo.v8.detect.predict.predict
+### ::: ultralytics.yolo.v8.detect.predict.predict
 <br><br>

docs/reference/yolo/v8/detect/train.md

@@ -3,12 +3,12 @@ description: Train and optimize custom object detection models with Ultralytics
 keywords: DetectionTrainer, Ultralytics YOLO, custom object detection, train models, AI applications
 ---
 
-# DetectionTrainer
+## DetectionTrainer
 ---
-:::ultralytics.yolo.v8.detect.train.DetectionTrainer
+### ::: ultralytics.yolo.v8.detect.train.DetectionTrainer
 <br><br>
 
-# train
+## train
 ---
-:::ultralytics.yolo.v8.detect.train.train
+### ::: ultralytics.yolo.v8.detect.train.train
 <br><br>

docs/reference/yolo/v8/detect/val.md

@@ -3,12 +3,12 @@ description: Validate YOLOv5 detections using this PyTorch module. Ensure model
 keywords: detection, validator, YOLOv5, object detection, model improvement, Ultralytics Docs
 ---
 
-# DetectionValidator
+## DetectionValidator
 ---
-:::ultralytics.yolo.v8.detect.val.DetectionValidator
+### ::: ultralytics.yolo.v8.detect.val.DetectionValidator
 <br><br>
 
-# val
+## val
 ---
-:::ultralytics.yolo.v8.detect.val.val
+### ::: ultralytics.yolo.v8.detect.val.val
 <br><br>

docs/reference/yolo/v8/pose/predict.md

@@ -3,12 +3,12 @@ description: Predict human pose coordinates and confidence scores using YOLOv5.
 keywords: Ultralytics, YOLO, v8, documentation, PosePredictor, pose prediction, pose estimation, predict method
 ---
 
-# PosePredictor
+## PosePredictor
 ---
-:::ultralytics.yolo.v8.pose.predict.PosePredictor
+### ::: ultralytics.yolo.v8.pose.predict.PosePredictor
 <br><br>
 
-# predict
+## predict
 ---
-:::ultralytics.yolo.v8.pose.predict.predict
+### ::: ultralytics.yolo.v8.pose.predict.predict
 <br><br>

docs/reference/yolo/v8/pose/train.md

@@ -3,12 +3,12 @@ description: Boost posture detection using PoseTrainer and train models using tr
 keywords: PoseTrainer, human pose models, deep learning, computer vision, Ultralytics YOLO, v8
 ---
 
-# PoseTrainer
+## PoseTrainer
 ---
-:::ultralytics.yolo.v8.pose.train.PoseTrainer
+### ::: ultralytics.yolo.v8.pose.train.PoseTrainer
 <br><br>
 
-# train
+## train
 ---
-:::ultralytics.yolo.v8.pose.train.train
+### ::: ultralytics.yolo.v8.pose.train.train
 <br><br>

docs/reference/yolo/v8/pose/val.md

@@ -3,12 +3,12 @@ description: Ensure proper human poses in images with YOLOv8 Pose Validation, pa
 keywords: PoseValidator, Ultralytics YOLO, object detection, pose analysis, validation
 ---
 
-# PoseValidator
+## PoseValidator
 ---
-:::ultralytics.yolo.v8.pose.val.PoseValidator
+### ::: ultralytics.yolo.v8.pose.val.PoseValidator
 <br><br>
 
-# val
+## val
 ---
-:::ultralytics.yolo.v8.pose.val.val
+### ::: ultralytics.yolo.v8.pose.val.val
 <br><br>

docs/reference/yolo/v8/segment/predict.md

@@ -3,12 +3,12 @@ description: '"Use SegmentationPredictor in YOLOv8 for efficient object detectio
 keywords: Ultralytics YOLO, SegmentationPredictor, object detection, segmentation masks, predict
 ---
 
-# SegmentationPredictor
+## SegmentationPredictor
 ---
-:::ultralytics.yolo.v8.segment.predict.SegmentationPredictor
+### ::: ultralytics.yolo.v8.segment.predict.SegmentationPredictor
 <br><br>
 
-# predict
+## predict
 ---
-:::ultralytics.yolo.v8.segment.predict.predict
+### ::: ultralytics.yolo.v8.segment.predict.predict
 <br><br>

docs/reference/yolo/v8/segment/train.md

@@ -3,12 +3,12 @@ description: Learn about SegmentationTrainer and Train in Ultralytics YOLO v8 fo
 keywords: SegmentationTrainer, Ultralytics YOLO, object detection, segmentation, train, tutorial, guide, code examples
 ---
 
-# SegmentationTrainer
+## SegmentationTrainer
 ---
-:::ultralytics.yolo.v8.segment.train.SegmentationTrainer
+### ::: ultralytics.yolo.v8.segment.train.SegmentationTrainer
 <br><br>
 
-# train
+## train
 ---
-:::ultralytics.yolo.v8.segment.train.train
+### ::: ultralytics.yolo.v8.segment.train.train
 <br><br>

docs/reference/yolo/v8/segment/val.md

@@ -3,12 +3,12 @@ description: Ensure segmentation quality on large datasets with SegmentationVali
 keywords: SegmentationValidator, YOLOv8, Ultralytics Docs, segmentation model, validation
 ---
 
-# SegmentationValidator
+## SegmentationValidator
 ---
-:::ultralytics.yolo.v8.segment.val.SegmentationValidator
+### ::: ultralytics.yolo.v8.segment.val.SegmentationValidator
 <br><br>
 
-# val
+## val
 ---
-:::ultralytics.yolo.v8.segment.val.val
+### ::: ultralytics.yolo.v8.segment.val.val
 <br><br>

docs/stylesheets/style.css

@@ -33,6 +33,7 @@ th, td {
 /* Table format like GitHub ----------------------------------------------------------------------------------------- */
 
 /* Code block vertical scroll */
-.md-typeset pre > code {
+div.highlight {
     max-height: 20rem;
+    overflow-y: auto; /* for adding a scrollbar when needed */
 }

ultralytics/nn/autobackend.py

@@ -54,8 +54,8 @@ class AutoBackend(nn.Module):
         Args:
             weights (str): The path to the weights file. Default: 'yolov8n.pt'
             device (torch.device): The device to run the model on.
-            dnn (bool): Use OpenCV's DNN module for inference if True, defaults to False.
-            data (str), (Path): Additional data.yaml file for class names, optional
+            dnn (bool): Use OpenCV DNN module for inference if True, defaults to False.
+            data (str | Path | optional): Additional data.yaml file for class names.
             fp16 (bool): If True, use half precision. Default: False
             fuse (bool): Whether to fuse the model or not. Default: True
             verbose (bool): Whether to run in verbose mode or not. Default: True

ultralytics/nn/autoshape.py

@@ -124,7 +124,8 @@ class AutoShape(nn.Module):
 
 
 class Detections:
-    # YOLOv8 detections class for inference results
+    """ YOLOv8 detections class for inference results"""
+
     def __init__(self, ims, pred, files, times=(0, 0, 0), names=None, shape=None):
         """Initialize object attributes for YOLO detection results."""
         super().__init__()

ultralytics/nn/tasks.py

@@ -190,7 +190,7 @@ class BaseModel(nn.Module):
         """Load the weights into the model.
 
         Args:
-            weights (dict) or (torch.nn.Module): The pre-trained weights to be loaded.
+            weights (dict | torch.nn.Module): The pre-trained weights to be loaded.
             verbose (bool, optional): Whether to log the transfer progress. Defaults to True.
         """
         model = weights['model'] if isinstance(weights, dict) else weights  # torchvision models are not dicts
@@ -701,7 +701,7 @@ def guess_model_scale(model_path):
     which is denoted by n, s, m, l, or x. The function returns the size character of the model scale as a string.
 
     Args:
-        model_path (str) or (Path): The path to the YOLO model's YAML file.
+        model_path (str | Path): The path to the YOLO model's YAML file.
 
     Returns:
         (str): The size character of the model's scale, which can be n, s, m, l, or x.
@@ -717,7 +717,7 @@ def guess_model_task(model):
     Guess the task of a PyTorch model from its architecture or configuration.
 
     Args:
-        model (nn.Module) or (dict): PyTorch model or model configuration in YAML format.
+        model (nn.Module | dict): PyTorch model or model configuration in YAML format.
 
     Returns:
         (str): Task of the model ('detect', 'segment', 'classify', 'pose').

ultralytics/yolo/cfg/__init__.py

@@ -80,8 +80,8 @@ def cfg2dict(cfg):
     """
     Convert a configuration object to a dictionary, whether it is a file path, a string, or a SimpleNamespace object.
 
-    Inputs:
-        cfg (str) or (Path) or (SimpleNamespace): Configuration object to be converted to a dictionary.
+    Args:
+        cfg (str | Path | SimpleNamespace): Configuration object to be converted to a dictionary.
 
     Returns:
         cfg (dict): Configuration object in dictionary format.
@@ -98,8 +98,8 @@ def get_cfg(cfg: Union[str, Path, Dict, SimpleNamespace] = DEFAULT_CFG_DICT, ove
     Load and merge configuration data from a file or dictionary.
 
     Args:
-        cfg (str) or (Path) or (Dict) or (SimpleNamespace): Configuration data.
-        overrides (str) or (Dict), optional: Overrides in the form of a file name or a dictionary. Default is None.
+        cfg (str | Path | Dict | SimpleNamespace): Configuration data.
+        overrides (str | Dict | optional): Overrides in the form of a file name or a dictionary. Default is None.
 
     Returns:
         (SimpleNamespace): Training arguments namespace.
@@ -168,9 +168,9 @@ def check_cfg_mismatch(base: Dict, custom: Dict, e=None):
     This function checks for any mismatched keys between a custom configuration list and a base configuration list.
     If any mismatched keys are found, the function prints out similar keys from the base list and exits the program.
 
-    Inputs:
-        - custom (Dict): a dictionary of custom configuration options
-        - base (Dict): a dictionary of base configuration options
+    Args:
+        custom (Dict): a dictionary of custom configuration options
+        base (Dict): a dictionary of base configuration options
     """
     custom = _handle_deprecation(custom)
     base, custom = (set(x.keys()) for x in (base, custom))

ultralytics/yolo/data/annotator.py

@@ -13,7 +13,7 @@ def auto_annotate(data, det_model='yolov8x.pt', sam_model='sam_b.pt', device='',
         det_model (str, optional): Pre-trained YOLO detection model. Defaults to 'yolov8x.pt'.
         sam_model (str, optional): Pre-trained SAM segmentation model. Defaults to 'sam_b.pt'.
         device (str, optional): Device to run the models on. Defaults to an empty string (CPU or GPU, if available).
-        output_dir (str, None, optional): Directory to save the annotated results.
+        output_dir (str | None | optional): Directory to save the annotated results.
             Defaults to a 'labels' folder in the same directory as 'data'.
     """
     device = select_device(device)

ultralytics/yolo/data/dataset.py

@@ -223,7 +223,7 @@ class ClassificationDataset(torchvision.datasets.ImageFolder):
             root (str): Dataset path.
             args (Namespace): Argument parser containing dataset related settings.
             augment (bool, optional): True if dataset should be augmented, False otherwise. Defaults to False.
-            cache (Union[bool, str], optional): Cache setting, can be True, False, 'ram' or 'disk'. Defaults to False.
+            cache (bool | str | optional): Cache setting, can be True, False, 'ram' or 'disk'. Defaults to False.
         """
         super().__init__(root=root)
         if augment and args.fraction < 1.0:  # reduce training fraction

ultralytics/yolo/engine/model.py

@@ -129,7 +129,7 @@ class YOLO:
 
         Args:
             cfg (str): model configuration file
-            task (str) or (None): model task
+            task (str | None): model task
             verbose (bool): display model info on load
         """
         cfg_dict = yaml_model_load(cfg)
@@ -149,7 +149,7 @@ class YOLO:
 
         Args:
             weights (str): model checkpoint to be loaded
-            task (str) or (None): model task
+            task (str | None): model task
         """
         suffix = Path(weights).suffix
         if suffix == '.pt':

ultralytics/yolo/engine/results.py

@@ -355,23 +355,23 @@ class Boxes(BaseTensor):
     A class for storing and manipulating detection boxes.
 
     Args:
-        boxes (torch.Tensor) or (numpy.ndarray): A tensor or numpy array containing the detection boxes,
+        boxes (torch.Tensor | numpy.ndarray): A tensor or numpy array containing the detection boxes,
             with shape (num_boxes, 6). The last two columns should contain confidence and class values.
         orig_shape (tuple): Original image size, in the format (height, width).
 
     Attributes:
-        boxes (torch.Tensor) or (numpy.ndarray): The detection boxes with shape (num_boxes, 6).
-        orig_shape (torch.Tensor) or (numpy.ndarray): Original image size, in the format (height, width).
+        boxes (torch.Tensor | numpy.ndarray): The detection boxes with shape (num_boxes, 6).
+        orig_shape (torch.Tensor | numpy.ndarray): Original image size, in the format (height, width).
         is_track (bool): True if the boxes also include track IDs, False otherwise.
 
     Properties:
-        xyxy (torch.Tensor) or (numpy.ndarray): The boxes in xyxy format.
-        conf (torch.Tensor) or (numpy.ndarray): The confidence values of the boxes.
-        cls (torch.Tensor) or (numpy.ndarray): The class values of the boxes.
-        id (torch.Tensor) or (numpy.ndarray): The track IDs of the boxes (if available).
-        xywh (torch.Tensor) or (numpy.ndarray): The boxes in xywh format.
-        xyxyn (torch.Tensor) or (numpy.ndarray): The boxes in xyxy format normalized by original image size.
-        xywhn (torch.Tensor) or (numpy.ndarray): The boxes in xywh format normalized by original image size.
+        xyxy (torch.Tensor | numpy.ndarray): The boxes in xyxy format.
+        conf (torch.Tensor | numpy.ndarray): The confidence values of the boxes.
+        cls (torch.Tensor | numpy.ndarray): The class values of the boxes.
+        id (torch.Tensor | numpy.ndarray): The track IDs of the boxes (if available).
+        xywh (torch.Tensor | numpy.ndarray): The boxes in xywh format.
+        xyxyn (torch.Tensor | numpy.ndarray): The boxes in xyxy format normalized by original image size.
+        xywhn (torch.Tensor | numpy.ndarray): The boxes in xywh format normalized by original image size.
         data (torch.Tensor): The raw bboxes tensor
 
     Methods:

ultralytics/yolo/utils/__init__.py

@@ -422,7 +422,7 @@ def is_dir_writeable(dir_path: Union[str, Path]) -> bool:
     Check if a directory is writeable.
 
     Args:
-        dir_path (str) or (Path): The path to the directory.
+        dir_path (str | Path): The path to the directory.
 
     Returns:
         (bool): True if the directory is writeable, False otherwise.
@@ -467,7 +467,7 @@ def get_git_dir():
     If the current file is not part of a git repository, returns None.
 
     Returns:
-        (Path) or (None): Git root directory if found or None if not found.
+        (Path | None): Git root directory if found or None if not found.
     """
     for d in Path(__file__).parents:
         if (d / '.git').is_dir():
@@ -480,7 +480,7 @@ def get_git_origin_url():
     Retrieves the origin URL of a git repository.
 
     Returns:
-        (str) or (None): The origin URL of the git repository.
+        (str | None): The origin URL of the git repository.
     """
     if is_git_dir():
         with contextlib.suppress(subprocess.CalledProcessError):
@@ -494,7 +494,7 @@ def get_git_branch():
     Returns the current git branch name. If not in a git repository, returns None.
 
     Returns:
-        (str) or (None): The current git branch name.
+        (str | None): The current git branch name.
     """
     if is_git_dir():
         with contextlib.suppress(subprocess.CalledProcessError):

ultralytics/yolo/utils/benchmarks.py

@@ -51,13 +51,13 @@ def benchmark(model=Path(SETTINGS['weights_dir']) / 'yolov8n.pt',
     Benchmark a YOLO model across different formats for speed and accuracy.
 
     Args:
-        model (Union[str, Path], optional): Path to the model file or directory. Default is
+        model (str | Path | optional): Path to the model file or directory. Default is
             Path(SETTINGS['weights_dir']) / 'yolov8n.pt'.
         imgsz (int, optional): Image size for the benchmark. Default is 160.
         half (bool, optional): Use half-precision for the model if True. Default is False.
         int8 (bool, optional): Use int8-precision for the model if True. Default is False.
         device (str, optional): Device to run the benchmark on, either 'cpu' or 'cuda'. Default is 'cpu'.
-        hard_fail (Union[bool, float], optional): If True or a float, assert benchmarks pass with given metric.
+        hard_fail (bool | float | optional): If True or a float, assert benchmarks pass with given metric.
             Default is False.
 
     Returns:

ultralytics/yolo/utils/checks.py

@@ -47,7 +47,7 @@ def check_imgsz(imgsz, stride=32, min_dim=1, max_dim=2, floor=0):
     stride, update it to the nearest multiple of the stride that is greater than or equal to the given floor value.
 
     Args:
-        imgsz (int) or (cList[int]): Image size.
+        imgsz (int | cList[int]): Image size.
         stride (int): Stride value.
         min_dim (int): Minimum number of dimensions.
         floor (int): Minimum allowed value for image size.

ultralytics/yolo/utils/instance.py

@@ -102,7 +102,7 @@ class Bboxes:
     def mul(self, scale):
         """
         Args:
-            scale (tuple) or (list) or (int): the scale for four coords.
+            scale (tuple | list | int): the scale for four coords.
         """
         if isinstance(scale, Number):
             scale = to_4tuple(scale)
@@ -116,7 +116,7 @@ class Bboxes:
     def add(self, offset):
         """
         Args:
-            offset (tuple) or (list) or (int): the offset for four coords.
+            offset (tuple | list | int): the offset for four coords.
         """
         if isinstance(offset, Number):
             offset = to_4tuple(offset)

ultralytics/yolo/utils/ops.py

@@ -123,7 +123,7 @@ def make_divisible(x, divisor):
 
     Args:
         x (int): The number to make divisible.
-        divisor (int) or (torch.Tensor): The divisor.
+        divisor (int | torch.Tensor): The divisor.
 
     Returns:
         (int): The nearest number divisible by the divisor.
@@ -166,7 +166,7 @@ def non_max_suppression(
             list contains the apriori labels for a given image. The list should be in the format
             output by a dataloader, with each label being a tuple of (class_index, x1, y1, x2, y2).
         max_det (int): The maximum number of boxes to keep after NMS.
-        nc (int): (optional) The number of classes output by the model. Any indices after this will be considered masks.
+        nc (int, optional): The number of classes output by the model. Any indices after this will be considered masks.
         max_time_img (float): The maximum time (seconds) for processing one image.
         max_nms (int): The maximum number of boxes into torchvision.ops.nms().
         max_wh (int): The maximum box width and height in pixels
@@ -290,7 +290,7 @@ def clip_coords(coords, shape):
     Clip line coordinates to the image boundaries.
 
     Args:
-        coords (torch.Tensor) or (numpy.ndarray): A list of line coordinates.
+        coords (torch.Tensor | numpy.ndarray): A list of line coordinates.
         shape (tuple): A tuple of integers representing the size of the image in the format (height, width).
 
     Returns:
@@ -347,9 +347,9 @@ def xyxy2xywh(x):
     Convert bounding box coordinates from (x1, y1, x2, y2) format to (x, y, width, height) format.
 
     Args:
-        x (np.ndarray) or (torch.Tensor): The input bounding box coordinates in (x1, y1, x2, y2) format.
+        x (np.ndarray | torch.Tensor): The input bounding box coordinates in (x1, y1, x2, y2) format.
     Returns:
-       y (np.ndarray) or (torch.Tensor): The bounding box coordinates in (x, y, width, height) format.
+       y (np.ndarray | torch.Tensor): The bounding box coordinates in (x, y, width, height) format.
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[..., 0] = (x[..., 0] + x[..., 2]) / 2  # x center
@@ -365,9 +365,9 @@ def xywh2xyxy(x):
     top-left corner and (x2, y2) is the bottom-right corner.
 
     Args:
-        x (np.ndarray) or (torch.Tensor): The input bounding box coordinates in (x, y, width, height) format.
+        x (np.ndarray | torch.Tensor): The input bounding box coordinates in (x, y, width, height) format.
     Returns:
-        y (np.ndarray) or (torch.Tensor): The bounding box coordinates in (x1, y1, x2, y2) format.
+        y (np.ndarray | torch.Tensor): The bounding box coordinates in (x1, y1, x2, y2) format.
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[..., 0] = x[..., 0] - x[..., 2] / 2  # top left x
@@ -382,13 +382,13 @@ def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
     Convert normalized bounding box coordinates to pixel coordinates.
 
     Args:
-        x (np.ndarray) or (torch.Tensor): The bounding box coordinates.
+        x (np.ndarray | torch.Tensor): The bounding box coordinates.
         w (int): Width of the image. Defaults to 640
         h (int): Height of the image. Defaults to 640
         padw (int): Padding width. Defaults to 0
         padh (int): Padding height. Defaults to 0
     Returns:
-        y (np.ndarray) or (torch.Tensor): The coordinates of the bounding box in the format [x1, y1, x2, y2] where
+        y (np.ndarray | torch.Tensor): The coordinates of the bounding box in the format [x1, y1, x2, y2] where
             x1,y1 is the top-left corner, x2,y2 is the bottom-right corner of the bounding box.
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
@@ -405,13 +405,13 @@ def xyxy2xywhn(x, w=640, h=640, clip=False, eps=0.0):
     x, y, width and height are normalized to image dimensions
 
     Args:
-        x (np.ndarray) or (torch.Tensor): The input bounding box coordinates in (x1, y1, x2, y2) format.
+        x (np.ndarray | torch.Tensor): The input bounding box coordinates in (x1, y1, x2, y2) format.
         w (int): The width of the image. Defaults to 640
         h (int): The height of the image. Defaults to 640
         clip (bool): If True, the boxes will be clipped to the image boundaries. Defaults to False
         eps (float): The minimum value of the box's width and height. Defaults to 0.0
     Returns:
-        y (np.ndarray) or (torch.Tensor): The bounding box coordinates in (x, y, width, height, normalized) format
+        y (np.ndarray | torch.Tensor): The bounding box coordinates in (x, y, width, height, normalized) format
     """
     if clip:
         clip_boxes(x, (h - eps, w - eps))  # warning: inplace clip
@@ -428,13 +428,13 @@ def xyn2xy(x, w=640, h=640, padw=0, padh=0):
     Convert normalized coordinates to pixel coordinates of shape (n,2)
 
     Args:
-        x (np.ndarray) or (torch.Tensor): The input tensor of normalized bounding box coordinates
+        x (np.ndarray | torch.Tensor): The input tensor of normalized bounding box coordinates
         w (int): The width of the image. Defaults to 640
         h (int): The height of the image. Defaults to 640
         padw (int): The width of the padding. Defaults to 0
         padh (int): The height of the padding. Defaults to 0
     Returns:
-        y (np.ndarray) or (torch.Tensor): The x and y coordinates of the top left corner of the bounding box
+        y (np.ndarray | torch.Tensor): The x and y coordinates of the top left corner of the bounding box
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[..., 0] = w * x[..., 0] + padw  # top left x
@@ -447,9 +447,9 @@ def xywh2ltwh(x):
     Convert the bounding box format from [x, y, w, h] to [x1, y1, w, h], where x1, y1 are the top-left coordinates.
 
     Args:
-        x (np.ndarray) or (torch.Tensor): The input tensor with the bounding box coordinates in the xywh format
+        x (np.ndarray | torch.Tensor): The input tensor with the bounding box coordinates in the xywh format
     Returns:
-        y (np.ndarray) or (torch.Tensor): The bounding box coordinates in the xyltwh format
+        y (np.ndarray | torch.Tensor): The bounding box coordinates in the xyltwh format
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[:, 0] = x[:, 0] - x[:, 2] / 2  # top left x
@@ -462,9 +462,9 @@ def xyxy2ltwh(x):
     Convert nx4 bounding boxes from [x1, y1, x2, y2] to [x1, y1, w, h], where xy1=top-left, xy2=bottom-right
 
     Args:
-      x (np.ndarray) or (torch.Tensor): The input tensor with the bounding boxes coordinates in the xyxy format
+      x (np.ndarray | torch.Tensor): The input tensor with the bounding boxes coordinates in the xyxy format
     Returns:
-      y (np.ndarray) or (torch.Tensor): The bounding box coordinates in the xyltwh format.
+      y (np.ndarray | torch.Tensor): The bounding box coordinates in the xyltwh format.
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[:, 2] = x[:, 2] - x[:, 0]  # width
@@ -490,10 +490,10 @@ def ltwh2xyxy(x):
     It converts the bounding box from [x1, y1, w, h] to [x1, y1, x2, y2] where xy1=top-left, xy2=bottom-right
 
     Args:
-      x (np.ndarray) or (torch.Tensor): the input image
+      x (np.ndarray | torch.Tensor): the input image
 
     Returns:
-      y (np.ndarray) or (torch.Tensor): the xyxy coordinates of the bounding boxes.
+      y (np.ndarray | torch.Tensor): the xyxy coordinates of the bounding boxes.
     """
     y = x.clone() if isinstance(x, torch.Tensor) else np.copy(x)
     y[:, 2] = x[:, 2] + x[:, 0]  # width