退购1.1定位算法

docs/reference/yolo/data/annotator.md

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+---
+description: Learn how to use auto_annotate in Ultralytics YOLO to generate annotations automatically for your dataset. Simplify object detection workflows.
+---
+
+# auto_annotate
+---
+:::ultralytics.yolo.data.annotator.auto_annotate
+<br><br>

docs/reference/yolo/data/augment.md

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+---
+description: Use Ultralytics YOLO Data Augmentation transforms with Base, MixUp, and Albumentations for object detection and classification.
+---
+
+# BaseTransform
+---
+:::ultralytics.yolo.data.augment.BaseTransform
+<br><br>
+
+# Compose
+---
+:::ultralytics.yolo.data.augment.Compose
+<br><br>
+
+# BaseMixTransform
+---
+:::ultralytics.yolo.data.augment.BaseMixTransform
+<br><br>
+
+# Mosaic
+---
+:::ultralytics.yolo.data.augment.Mosaic
+<br><br>
+
+# MixUp
+---
+:::ultralytics.yolo.data.augment.MixUp
+<br><br>
+
+# RandomPerspective
+---
+:::ultralytics.yolo.data.augment.RandomPerspective
+<br><br>
+
+# RandomHSV
+---
+:::ultralytics.yolo.data.augment.RandomHSV
+<br><br>
+
+# RandomFlip
+---
+:::ultralytics.yolo.data.augment.RandomFlip
+<br><br>
+
+# LetterBox
+---
+:::ultralytics.yolo.data.augment.LetterBox
+<br><br>
+
+# CopyPaste
+---
+:::ultralytics.yolo.data.augment.CopyPaste
+<br><br>
+
+# Albumentations
+---
+:::ultralytics.yolo.data.augment.Albumentations
+<br><br>
+
+# Format
+---
+:::ultralytics.yolo.data.augment.Format
+<br><br>
+
+# ClassifyLetterBox
+---
+:::ultralytics.yolo.data.augment.ClassifyLetterBox
+<br><br>
+
+# CenterCrop
+---
+:::ultralytics.yolo.data.augment.CenterCrop
+<br><br>
+
+# ToTensor
+---
+:::ultralytics.yolo.data.augment.ToTensor
+<br><br>
+
+# v8_transforms
+---
+:::ultralytics.yolo.data.augment.v8_transforms
+<br><br>
+
+# classify_transforms
+---
+:::ultralytics.yolo.data.augment.classify_transforms
+<br><br>
+
+# classify_albumentations
+---
+:::ultralytics.yolo.data.augment.classify_albumentations
+<br><br>

docs/reference/yolo/data/base.md

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+---
+description: Learn about BaseDataset in Ultralytics YOLO, a flexible dataset class for object detection. Maximize your YOLO performance with custom datasets.
+---
+
+# BaseDataset
+---
+:::ultralytics.yolo.data.base.BaseDataset
+<br><br>

docs/reference/yolo/data/build.md

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+---
+description: Maximize YOLO performance with Ultralytics' InfiniteDataLoader, seed_worker, build_dataloader, and load_inference_source functions.
+---
+
+# InfiniteDataLoader
+---
+:::ultralytics.yolo.data.build.InfiniteDataLoader
+<br><br>
+
+# _RepeatSampler
+---
+:::ultralytics.yolo.data.build._RepeatSampler
+<br><br>
+
+# seed_worker
+---
+:::ultralytics.yolo.data.build.seed_worker
+<br><br>
+
+# build_yolo_dataset
+---
+:::ultralytics.yolo.data.build.build_yolo_dataset
+<br><br>
+
+# build_dataloader
+---
+:::ultralytics.yolo.data.build.build_dataloader
+<br><br>
+
+# check_source
+---
+:::ultralytics.yolo.data.build.check_source
+<br><br>
+
+# load_inference_source
+---
+:::ultralytics.yolo.data.build.load_inference_source
+<br><br>

docs/reference/yolo/data/converter.md

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+---
+description: Convert COCO-91 to COCO-80 class, RLE to polygon, and merge multi-segment images with Ultralytics YOLO data converter. Improve your object detection.
+---
+
+# coco91_to_coco80_class
+---
+:::ultralytics.yolo.data.converter.coco91_to_coco80_class
+<br><br>
+
+# convert_coco
+---
+:::ultralytics.yolo.data.converter.convert_coco
+<br><br>
+
+# rle2polygon
+---
+:::ultralytics.yolo.data.converter.rle2polygon
+<br><br>
+
+# min_index
+---
+:::ultralytics.yolo.data.converter.min_index
+<br><br>
+
+# merge_multi_segment
+---
+:::ultralytics.yolo.data.converter.merge_multi_segment
+<br><br>
+
+# delete_dsstore
+---
+:::ultralytics.yolo.data.converter.delete_dsstore
+<br><br>

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

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+---
+description: 'Ultralytics YOLO Docs: Learn about stream loaders for image and tensor data, as well as autocasting techniques. Check out SourceTypes and more.'
+---
+
+# SourceTypes
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.SourceTypes
+<br><br>
+
+# LoadStreams
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadStreams
+<br><br>
+
+# LoadScreenshots
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadScreenshots
+<br><br>
+
+# LoadImages
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadImages
+<br><br>
+
+# LoadPilAndNumpy
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadPilAndNumpy
+<br><br>
+
+# LoadTensor
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.LoadTensor
+<br><br>
+
+# autocast_list
+---
+:::ultralytics.yolo.data.dataloaders.stream_loaders.autocast_list
+<br><br>

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

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+---
+description: Enhance image data with Albumentations CenterCrop, normalize, augment_hsv, replicate, random_perspective, cutout, & box_candidates.
+---
+
+# Albumentations
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.Albumentations
+<br><br>
+
+# LetterBox
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.LetterBox
+<br><br>
+
+# CenterCrop
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.CenterCrop
+<br><br>
+
+# ToTensor
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.ToTensor
+<br><br>
+
+# normalize
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.normalize
+<br><br>
+
+# denormalize
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.denormalize
+<br><br>
+
+# augment_hsv
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.augment_hsv
+<br><br>
+
+# hist_equalize
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.hist_equalize
+<br><br>
+
+# replicate
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.replicate
+<br><br>
+
+# letterbox
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.letterbox
+<br><br>
+
+# random_perspective
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.random_perspective
+<br><br>
+
+# copy_paste
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.copy_paste
+<br><br>
+
+# cutout
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.cutout
+<br><br>
+
+# mixup
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.mixup
+<br><br>
+
+# box_candidates
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.box_candidates
+<br><br>
+
+# classify_albumentations
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.classify_albumentations
+<br><br>
+
+# classify_transforms
+---
+:::ultralytics.yolo.data.dataloaders.v5augmentations.classify_transforms
+<br><br>

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

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+---
+description: Efficiently load images and labels to models using Ultralytics YOLO's InfiniteDataLoader, LoadScreenshots, and LoadStreams.
+---
+
+# InfiniteDataLoader
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.InfiniteDataLoader
+<br><br>
+
+# _RepeatSampler
+---
+:::ultralytics.yolo.data.dataloaders.v5loader._RepeatSampler
+<br><br>
+
+# LoadScreenshots
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.LoadScreenshots
+<br><br>
+
+# LoadImages
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.LoadImages
+<br><br>
+
+# LoadStreams
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.LoadStreams
+<br><br>
+
+# LoadImagesAndLabels
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.LoadImagesAndLabels
+<br><br>
+
+# ClassificationDataset
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.ClassificationDataset
+<br><br>
+
+# get_hash
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.get_hash
+<br><br>
+
+# exif_size
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.exif_size
+<br><br>
+
+# exif_transpose
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.exif_transpose
+<br><br>
+
+# seed_worker
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.seed_worker
+<br><br>
+
+# create_dataloader
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.create_dataloader
+<br><br>
+
+# img2label_paths
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.img2label_paths
+<br><br>
+
+# flatten_recursive
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.flatten_recursive
+<br><br>
+
+# extract_boxes
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.extract_boxes
+<br><br>
+
+# autosplit
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.autosplit
+<br><br>
+
+# verify_image_label
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.verify_image_label
+<br><br>
+
+# create_classification_dataloader
+---
+:::ultralytics.yolo.data.dataloaders.v5loader.create_classification_dataloader
+<br><br>

docs/reference/yolo/data/dataset.md

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+---
+description: Create custom YOLOv5 datasets with Ultralytics YOLODataset and SemanticDataset. Streamline your object detection and segmentation projects.
+---
+
+# YOLODataset
+---
+:::ultralytics.yolo.data.dataset.YOLODataset
+<br><br>
+
+# ClassificationDataset
+---
+:::ultralytics.yolo.data.dataset.ClassificationDataset
+<br><br>
+
+# SemanticDataset
+---
+:::ultralytics.yolo.data.dataset.SemanticDataset
+<br><br>

docs/reference/yolo/data/dataset_wrappers.md

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+---
+description: Create a custom dataset of mixed and oriented rectangular objects with Ultralytics YOLO's MixAndRectDataset.
+---
+
+# MixAndRectDataset
+---
+:::ultralytics.yolo.data.dataset_wrappers.MixAndRectDataset
+<br><br>

docs/reference/yolo/data/utils.md

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+---
+description: Efficiently handle data in YOLO with Ultralytics. Utilize HUBDatasetStats and customize dataset with these data utility functions.
+---
+
+# HUBDatasetStats
+---
+:::ultralytics.yolo.data.utils.HUBDatasetStats
+<br><br>
+
+# img2label_paths
+---
+:::ultralytics.yolo.data.utils.img2label_paths
+<br><br>
+
+# get_hash
+---
+:::ultralytics.yolo.data.utils.get_hash
+<br><br>
+
+# exif_size
+---
+:::ultralytics.yolo.data.utils.exif_size
+<br><br>
+
+# verify_image_label
+---
+:::ultralytics.yolo.data.utils.verify_image_label
+<br><br>
+
+# polygon2mask
+---
+:::ultralytics.yolo.data.utils.polygon2mask
+<br><br>
+
+# polygons2masks
+---
+:::ultralytics.yolo.data.utils.polygons2masks
+<br><br>
+
+# polygons2masks_overlap
+---
+:::ultralytics.yolo.data.utils.polygons2masks_overlap
+<br><br>
+
+# check_det_dataset
+---
+:::ultralytics.yolo.data.utils.check_det_dataset
+<br><br>
+
+# check_cls_dataset
+---
+:::ultralytics.yolo.data.utils.check_cls_dataset
+<br><br>
+
+# compress_one_image
+---
+:::ultralytics.yolo.data.utils.compress_one_image
+<br><br>
+
+# delete_dsstore
+---
+:::ultralytics.yolo.data.utils.delete_dsstore
+<br><br>
+
+# zip_directory
+---
+:::ultralytics.yolo.data.utils.zip_directory
+<br><br>

docs/reference/yolo/engine/exporter.md

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+---
+description: Learn how to export your YOLO model in various formats using Ultralytics' exporter package - iOS, GDC, and more.
+---
+
+# Exporter
+---
+:::ultralytics.yolo.engine.exporter.Exporter
+<br><br>
+
+# iOSDetectModel
+---
+:::ultralytics.yolo.engine.exporter.iOSDetectModel
+<br><br>
+
+# export_formats
+---
+:::ultralytics.yolo.engine.exporter.export_formats
+<br><br>
+
+# gd_outputs
+---
+:::ultralytics.yolo.engine.exporter.gd_outputs
+<br><br>
+
+# try_export
+---
+:::ultralytics.yolo.engine.exporter.try_export
+<br><br>
+
+# export
+---
+:::ultralytics.yolo.engine.exporter.export
+<br><br>

docs/reference/yolo/engine/model.md

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+---
+description: Discover the YOLO model of Ultralytics engine to simplify your object detection tasks with state-of-the-art models.
+---
+
+# YOLO
+---
+:::ultralytics.yolo.engine.model.YOLO
+<br><br>

docs/reference/yolo/engine/predictor.md

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+---
+description: '"The BasePredictor class in Ultralytics YOLO Engine predicts object detection in images and videos. Learn to implement YOLO with ease."'
+---
+
+# BasePredictor
+---
+:::ultralytics.yolo.engine.predictor.BasePredictor
+<br><br>

docs/reference/yolo/engine/results.md

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+---
+description: Learn about BaseTensor & Boxes in Ultralytics YOLO Engine. Check out Ultralytics Docs for quality tutorials and resources on object detection.
+---
+
+# BaseTensor
+---
+:::ultralytics.yolo.engine.results.BaseTensor
+<br><br>
+
+# Results
+---
+:::ultralytics.yolo.engine.results.Results
+<br><br>
+
+# Boxes
+---
+:::ultralytics.yolo.engine.results.Boxes
+<br><br>
+
+# Masks
+---
+:::ultralytics.yolo.engine.results.Masks
+<br><br>

docs/reference/yolo/engine/trainer.md

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+---
+description: Train faster with mixed precision. Learn how to use BaseTrainer with Advanced Mixed Precision to optimize YOLOv3 and YOLOv4 models.
+---
+
+# BaseTrainer
+---
+:::ultralytics.yolo.engine.trainer.BaseTrainer
+<br><br>
+
+# check_amp
+---
+:::ultralytics.yolo.engine.trainer.check_amp
+<br><br>

docs/reference/yolo/engine/validator.md

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+---
+description: Ensure YOLOv5 models meet constraints and standards with the BaseValidator class. Learn how to use it here.
+---
+
+# BaseValidator
+---
+:::ultralytics.yolo.engine.validator.BaseValidator
+<br><br>

docs/reference/yolo/utils/autobatch.md

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+---
+description: Dynamically adjusts input size to optimize GPU memory usage during training. Learn how to use check_train_batch_size with Ultralytics YOLO.
+---
+
+# check_train_batch_size
+---
+:::ultralytics.yolo.utils.autobatch.check_train_batch_size
+<br><br>
+
+# autobatch
+---
+:::ultralytics.yolo.utils.autobatch.autobatch
+<br><br>

docs/reference/yolo/utils/benchmarks.md

@@ -0,0 +1,8 @@
+---
+description: Improve your YOLO's performance and measure its speed. Benchmark utility for YOLOv5.
+---
+
+# benchmark
+---
+:::ultralytics.yolo.utils.benchmarks.benchmark
+<br><br>

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

@@ -0,0 +1,138 @@
+---
+description: Learn about YOLO's callback functions from on_train_start to add_integration_callbacks. See how these callbacks modify and save models.
+---
+
+# on_pretrain_routine_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_pretrain_routine_start
+<br><br>
+
+# on_pretrain_routine_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_pretrain_routine_end
+<br><br>
+
+# on_train_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_train_start
+<br><br>
+
+# on_train_epoch_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_train_epoch_start
+<br><br>
+
+# on_train_batch_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_train_batch_start
+<br><br>
+
+# optimizer_step
+---
+:::ultralytics.yolo.utils.callbacks.base.optimizer_step
+<br><br>
+
+# on_before_zero_grad
+---
+:::ultralytics.yolo.utils.callbacks.base.on_before_zero_grad
+<br><br>
+
+# on_train_batch_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_train_batch_end
+<br><br>
+
+# on_train_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_train_epoch_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_fit_epoch_end
+<br><br>
+
+# on_model_save
+---
+:::ultralytics.yolo.utils.callbacks.base.on_model_save
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_train_end
+<br><br>
+
+# on_params_update
+---
+:::ultralytics.yolo.utils.callbacks.base.on_params_update
+<br><br>
+
+# teardown
+---
+:::ultralytics.yolo.utils.callbacks.base.teardown
+<br><br>
+
+# on_val_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_val_start
+<br><br>
+
+# on_val_batch_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_val_batch_start
+<br><br>
+
+# on_val_batch_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_val_batch_end
+<br><br>
+
+# on_val_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_val_end
+<br><br>
+
+# on_predict_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_predict_start
+<br><br>
+
+# on_predict_batch_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_predict_batch_start
+<br><br>
+
+# on_predict_batch_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_predict_batch_end
+<br><br>
+
+# on_predict_postprocess_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_predict_postprocess_end
+<br><br>
+
+# on_predict_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_predict_end
+<br><br>
+
+# on_export_start
+---
+:::ultralytics.yolo.utils.callbacks.base.on_export_start
+<br><br>
+
+# on_export_end
+---
+:::ultralytics.yolo.utils.callbacks.base.on_export_end
+<br><br>
+
+# get_default_callbacks
+---
+:::ultralytics.yolo.utils.callbacks.base.get_default_callbacks
+<br><br>
+
+# add_integration_callbacks
+---
+:::ultralytics.yolo.utils.callbacks.base.add_integration_callbacks
+<br><br>

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

@@ -0,0 +1,38 @@
+---
+description: Improve your YOLOv5 model training with callbacks from ClearML. Learn about log debug samples, pre-training routines, validation and more.
+---
+
+# _log_debug_samples
+---
+:::ultralytics.yolo.utils.callbacks.clearml._log_debug_samples
+<br><br>
+
+# _log_plot
+---
+:::ultralytics.yolo.utils.callbacks.clearml._log_plot
+<br><br>
+
+# on_pretrain_routine_start
+---
+:::ultralytics.yolo.utils.callbacks.clearml.on_pretrain_routine_start
+<br><br>
+
+# on_train_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.clearml.on_train_epoch_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.clearml.on_fit_epoch_end
+<br><br>
+
+# on_val_end
+---
+:::ultralytics.yolo.utils.callbacks.clearml.on_val_end
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.clearml.on_train_end
+<br><br>

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

@@ -0,0 +1,123 @@
+---
+description: Learn about YOLO callbacks using the Comet.ml platform, enhancing object detection training and testing with custom logging and visualizations.
+---
+
+# _get_comet_mode
+---
+:::ultralytics.yolo.utils.callbacks.comet._get_comet_mode
+<br><br>
+
+# _get_comet_model_name
+---
+:::ultralytics.yolo.utils.callbacks.comet._get_comet_model_name
+<br><br>
+
+# _get_eval_batch_logging_interval
+---
+:::ultralytics.yolo.utils.callbacks.comet._get_eval_batch_logging_interval
+<br><br>
+
+# _get_max_image_predictions_to_log
+---
+:::ultralytics.yolo.utils.callbacks.comet._get_max_image_predictions_to_log
+<br><br>
+
+# _scale_confidence_score
+---
+:::ultralytics.yolo.utils.callbacks.comet._scale_confidence_score
+<br><br>
+
+# _should_log_confusion_matrix
+---
+:::ultralytics.yolo.utils.callbacks.comet._should_log_confusion_matrix
+<br><br>
+
+# _should_log_image_predictions
+---
+:::ultralytics.yolo.utils.callbacks.comet._should_log_image_predictions
+<br><br>
+
+# _get_experiment_type
+---
+:::ultralytics.yolo.utils.callbacks.comet._get_experiment_type
+<br><br>
+
+# _create_experiment
+---
+:::ultralytics.yolo.utils.callbacks.comet._create_experiment
+<br><br>
+
+# _fetch_trainer_metadata
+---
+:::ultralytics.yolo.utils.callbacks.comet._fetch_trainer_metadata
+<br><br>
+
+# _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
+---
+:::ultralytics.yolo.utils.callbacks.comet._format_ground_truth_annotations_for_detection
+<br><br>
+
+# _format_prediction_annotations_for_detection
+---
+:::ultralytics.yolo.utils.callbacks.comet._format_prediction_annotations_for_detection
+<br><br>
+
+# _fetch_annotations
+---
+:::ultralytics.yolo.utils.callbacks.comet._fetch_annotations
+<br><br>
+
+# _create_prediction_metadata_map
+---
+:::ultralytics.yolo.utils.callbacks.comet._create_prediction_metadata_map
+<br><br>
+
+# _log_confusion_matrix
+---
+:::ultralytics.yolo.utils.callbacks.comet._log_confusion_matrix
+<br><br>
+
+# _log_images
+---
+:::ultralytics.yolo.utils.callbacks.comet._log_images
+<br><br>
+
+# _log_image_predictions
+---
+:::ultralytics.yolo.utils.callbacks.comet._log_image_predictions
+<br><br>
+
+# _log_plots
+---
+:::ultralytics.yolo.utils.callbacks.comet._log_plots
+<br><br>
+
+# _log_model
+---
+:::ultralytics.yolo.utils.callbacks.comet._log_model
+<br><br>
+
+# on_pretrain_routine_start
+---
+:::ultralytics.yolo.utils.callbacks.comet.on_pretrain_routine_start
+<br><br>
+
+# on_train_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.comet.on_train_epoch_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.comet.on_fit_epoch_end
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.comet.on_train_end
+<br><br>

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

@@ -0,0 +1,43 @@
+---
+description: Improve YOLOv5 model training with Ultralytics' on-train callbacks. Boost performance on-pretrain-routine-end, model-save, train/predict start.
+---
+
+# on_pretrain_routine_end
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_pretrain_routine_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_fit_epoch_end
+<br><br>
+
+# on_model_save
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_model_save
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_train_end
+<br><br>
+
+# on_train_start
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_train_start
+<br><br>
+
+# on_val_start
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_val_start
+<br><br>
+
+# on_predict_start
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_predict_start
+<br><br>
+
+# on_export_start
+---
+:::ultralytics.yolo.utils.callbacks.hub.on_export_start
+<br><br>

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

@@ -0,0 +1,18 @@
+---
+description: Track model performance and metrics with MLflow in YOLOv5. Use callbacks like on_pretrain_routine_end or on_train_end to log information.
+---
+
+# on_pretrain_routine_end
+---
+:::ultralytics.yolo.utils.callbacks.mlflow.on_pretrain_routine_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.mlflow.on_fit_epoch_end
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.mlflow.on_train_end
+<br><br>

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

@@ -0,0 +1,43 @@
+---
+description: Improve YOLOv5 training with Neptune, a powerful logging tool. Track metrics like images, plots, and epochs for better model performance.
+---
+
+# _log_scalars
+---
+:::ultralytics.yolo.utils.callbacks.neptune._log_scalars
+<br><br>
+
+# _log_images
+---
+:::ultralytics.yolo.utils.callbacks.neptune._log_images
+<br><br>
+
+# _log_plot
+---
+:::ultralytics.yolo.utils.callbacks.neptune._log_plot
+<br><br>
+
+# on_pretrain_routine_start
+---
+:::ultralytics.yolo.utils.callbacks.neptune.on_pretrain_routine_start
+<br><br>
+
+# on_train_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.neptune.on_train_epoch_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.neptune.on_fit_epoch_end
+<br><br>
+
+# on_val_end
+---
+:::ultralytics.yolo.utils.callbacks.neptune.on_val_end
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.neptune.on_train_end
+<br><br>

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

@@ -0,0 +1,8 @@
+---
+description: '"Improve YOLO model performance with on_fit_epoch_end callback. Learn to integrate with Ray Tune for hyperparameter tuning. Ultralytics YOLO docs."'
+---
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.raytune.on_fit_epoch_end
+<br><br>

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

@@ -0,0 +1,23 @@
+---
+description: Learn how to monitor the training process with Tensorboard using Ultralytics YOLO's "_log_scalars" and "on_batch_end" methods.
+---
+
+# _log_scalars
+---
+:::ultralytics.yolo.utils.callbacks.tensorboard._log_scalars
+<br><br>
+
+# on_pretrain_routine_start
+---
+:::ultralytics.yolo.utils.callbacks.tensorboard.on_pretrain_routine_start
+<br><br>
+
+# on_batch_end
+---
+:::ultralytics.yolo.utils.callbacks.tensorboard.on_batch_end
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.tensorboard.on_fit_epoch_end
+<br><br>

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

@@ -0,0 +1,23 @@
+---
+description: Learn how to use Ultralytics YOLO's built-in callbacks `on_pretrain_routine_start` and `on_train_epoch_end` for improved training performance.
+---
+
+# on_pretrain_routine_start
+---
+:::ultralytics.yolo.utils.callbacks.wb.on_pretrain_routine_start
+<br><br>
+
+# on_fit_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.wb.on_fit_epoch_end
+<br><br>
+
+# on_train_epoch_end
+---
+:::ultralytics.yolo.utils.callbacks.wb.on_train_epoch_end
+<br><br>
+
+# on_train_end
+---
+:::ultralytics.yolo.utils.callbacks.wb.on_train_end
+<br><br>

docs/reference/yolo/utils/checks.md

@@ -0,0 +1,83 @@
+---
+description: 'Check functions for YOLO utils: image size, version, font, requirements, filename suffix, YAML file, YOLO, and Git version.'
+---
+
+# is_ascii
+---
+:::ultralytics.yolo.utils.checks.is_ascii
+<br><br>
+
+# check_imgsz
+---
+:::ultralytics.yolo.utils.checks.check_imgsz
+<br><br>
+
+# check_version
+---
+:::ultralytics.yolo.utils.checks.check_version
+<br><br>
+
+# check_latest_pypi_version
+---
+:::ultralytics.yolo.utils.checks.check_latest_pypi_version
+<br><br>
+
+# check_pip_update_available
+---
+:::ultralytics.yolo.utils.checks.check_pip_update_available
+<br><br>
+
+# check_font
+---
+:::ultralytics.yolo.utils.checks.check_font
+<br><br>
+
+# check_python
+---
+:::ultralytics.yolo.utils.checks.check_python
+<br><br>
+
+# check_requirements
+---
+:::ultralytics.yolo.utils.checks.check_requirements
+<br><br>
+
+# check_suffix
+---
+:::ultralytics.yolo.utils.checks.check_suffix
+<br><br>
+
+# check_yolov5u_filename
+---
+:::ultralytics.yolo.utils.checks.check_yolov5u_filename
+<br><br>
+
+# check_file
+---
+:::ultralytics.yolo.utils.checks.check_file
+<br><br>
+
+# check_yaml
+---
+:::ultralytics.yolo.utils.checks.check_yaml
+<br><br>
+
+# check_imshow
+---
+:::ultralytics.yolo.utils.checks.check_imshow
+<br><br>
+
+# check_yolo
+---
+:::ultralytics.yolo.utils.checks.check_yolo
+<br><br>
+
+# git_describe
+---
+:::ultralytics.yolo.utils.checks.git_describe
+<br><br>
+
+# print_args
+---
+:::ultralytics.yolo.utils.checks.print_args
+<br><br>

docs/reference/yolo/utils/dist.md

@@ -0,0 +1,23 @@
+---
+description: Learn how to find free network port and generate DDP (Distributed Data Parallel) command in Ultralytics YOLO with easy examples.
+---
+
+# find_free_network_port
+---
+:::ultralytics.yolo.utils.dist.find_free_network_port
+<br><br>
+
+# generate_ddp_file
+---
+:::ultralytics.yolo.utils.dist.generate_ddp_file
+<br><br>
+
+# generate_ddp_command
+---
+:::ultralytics.yolo.utils.dist.generate_ddp_command
+<br><br>
+
+# ddp_cleanup
+---
+:::ultralytics.yolo.utils.dist.ddp_cleanup
+<br><br>

docs/reference/yolo/utils/downloads.md

@@ -0,0 +1,33 @@
+---
+description: Download and unzip YOLO pretrained models. Ultralytics YOLO docs utils.downloads.unzip_file, checks disk space, downloads and attempts assets.
+---
+
+# is_url
+---
+:::ultralytics.yolo.utils.downloads.is_url
+<br><br>
+
+# unzip_file
+---
+:::ultralytics.yolo.utils.downloads.unzip_file
+<br><br>
+
+# check_disk_space
+---
+:::ultralytics.yolo.utils.downloads.check_disk_space
+<br><br>
+
+# safe_download
+---
+:::ultralytics.yolo.utils.downloads.safe_download
+<br><br>
+
+# attempt_download_asset
+---
+:::ultralytics.yolo.utils.downloads.attempt_download_asset
+<br><br>
+
+# download
+---
+:::ultralytics.yolo.utils.downloads.download
+<br><br>

docs/reference/yolo/utils/errors.md

@@ -0,0 +1,8 @@
+---
+description: Learn about HUBModelError in Ultralytics YOLO Docs. Resolve the error and get the most out of your YOLO model.
+---
+
+# HUBModelError
+---
+:::ultralytics.yolo.utils.errors.HUBModelError
+<br><br>

docs/reference/yolo/utils/files.md

@@ -0,0 +1,38 @@
+---
+description: 'Learn about Ultralytics YOLO files and directory utilities: WorkingDirectory, file_age, file_size, and make_dirs.'
+---
+
+# WorkingDirectory
+---
+:::ultralytics.yolo.utils.files.WorkingDirectory
+<br><br>
+
+# increment_path
+---
+:::ultralytics.yolo.utils.files.increment_path
+<br><br>
+
+# file_age
+---
+:::ultralytics.yolo.utils.files.file_age
+<br><br>
+
+# file_date
+---
+:::ultralytics.yolo.utils.files.file_date
+<br><br>
+
+# file_size
+---
+:::ultralytics.yolo.utils.files.file_size
+<br><br>
+
+# get_latest_run
+---
+:::ultralytics.yolo.utils.files.get_latest_run
+<br><br>
+
+# make_dirs
+---
+:::ultralytics.yolo.utils.files.make_dirs
+<br><br>

docs/reference/yolo/utils/instance.md

@@ -0,0 +1,18 @@
+---
+description: Learn about Bounding Boxes (Bboxes) and _ntuple in Ultralytics YOLO for object detection. Improve accuracy and speed with these powerful tools.
+---
+
+# Bboxes
+---
+:::ultralytics.yolo.utils.instance.Bboxes
+<br><br>
+
+# Instances
+---
+:::ultralytics.yolo.utils.instance.Instances
+<br><br>
+
+# _ntuple
+---
+:::ultralytics.yolo.utils.instance._ntuple
+<br><br>

docs/reference/yolo/utils/loss.md

@@ -0,0 +1,18 @@
+---
+description: Learn about Varifocal Loss and Keypoint Loss in Ultralytics YOLO for advanced bounding box and pose estimation. Visit our docs for more.
+---
+
+# VarifocalLoss
+---
+:::ultralytics.yolo.utils.loss.VarifocalLoss
+<br><br>
+
+# BboxLoss
+---
+:::ultralytics.yolo.utils.loss.BboxLoss
+<br><br>
+
+# KeypointLoss
+---
+:::ultralytics.yolo.utils.loss.KeypointLoss
+<br><br>

docs/reference/yolo/utils/metrics.md

@@ -0,0 +1,98 @@
+---
+description: Explore Ultralytics YOLO's FocalLoss, DetMetrics, PoseMetrics, ClassifyMetrics, and more with Ultralytics Metrics documentation.
+---
+
+# FocalLoss
+---
+:::ultralytics.yolo.utils.metrics.FocalLoss
+<br><br>
+
+# ConfusionMatrix
+---
+:::ultralytics.yolo.utils.metrics.ConfusionMatrix
+<br><br>
+
+# Metric
+---
+:::ultralytics.yolo.utils.metrics.Metric
+<br><br>
+
+# DetMetrics
+---
+:::ultralytics.yolo.utils.metrics.DetMetrics
+<br><br>
+
+# SegmentMetrics
+---
+:::ultralytics.yolo.utils.metrics.SegmentMetrics
+<br><br>
+
+# PoseMetrics
+---
+:::ultralytics.yolo.utils.metrics.PoseMetrics
+<br><br>
+
+# ClassifyMetrics
+---
+:::ultralytics.yolo.utils.metrics.ClassifyMetrics
+<br><br>
+
+# box_area
+---
+:::ultralytics.yolo.utils.metrics.box_area
+<br><br>
+
+# bbox_ioa
+---
+:::ultralytics.yolo.utils.metrics.bbox_ioa
+<br><br>
+
+# box_iou
+---
+:::ultralytics.yolo.utils.metrics.box_iou
+<br><br>
+
+# bbox_iou
+---
+:::ultralytics.yolo.utils.metrics.bbox_iou
+<br><br>
+
+# mask_iou
+---
+:::ultralytics.yolo.utils.metrics.mask_iou
+<br><br>
+
+# kpt_iou
+---
+:::ultralytics.yolo.utils.metrics.kpt_iou
+<br><br>
+
+# smooth_BCE
+---
+:::ultralytics.yolo.utils.metrics.smooth_BCE
+<br><br>
+
+# smooth
+---
+:::ultralytics.yolo.utils.metrics.smooth
+<br><br>
+
+# plot_pr_curve
+---
+:::ultralytics.yolo.utils.metrics.plot_pr_curve
+<br><br>
+
+# plot_mc_curve
+---
+:::ultralytics.yolo.utils.metrics.plot_mc_curve
+<br><br>
+
+# compute_ap
+---
+:::ultralytics.yolo.utils.metrics.compute_ap
+<br><br>
+
+# ap_per_class
+---
+:::ultralytics.yolo.utils.metrics.ap_per_class
+<br><br>

docs/reference/yolo/utils/ops.md

@@ -0,0 +1,138 @@
+---
+description: Learn about various utility functions in Ultralytics YOLO, including x, y, width, height conversions, non-max suppression, and more.
+---
+
+# Profile
+---
+:::ultralytics.yolo.utils.ops.Profile
+<br><br>
+
+# coco80_to_coco91_class
+---
+:::ultralytics.yolo.utils.ops.coco80_to_coco91_class
+<br><br>
+
+# segment2box
+---
+:::ultralytics.yolo.utils.ops.segment2box
+<br><br>
+
+# scale_boxes
+---
+:::ultralytics.yolo.utils.ops.scale_boxes
+<br><br>
+
+# make_divisible
+---
+:::ultralytics.yolo.utils.ops.make_divisible
+<br><br>
+
+# non_max_suppression
+---
+:::ultralytics.yolo.utils.ops.non_max_suppression
+<br><br>
+
+# clip_boxes
+---
+:::ultralytics.yolo.utils.ops.clip_boxes
+<br><br>
+
+# clip_coords
+---
+:::ultralytics.yolo.utils.ops.clip_coords
+<br><br>
+
+# scale_image
+---
+:::ultralytics.yolo.utils.ops.scale_image
+<br><br>
+
+# xyxy2xywh
+---
+:::ultralytics.yolo.utils.ops.xyxy2xywh
+<br><br>
+
+# xywh2xyxy
+---
+:::ultralytics.yolo.utils.ops.xywh2xyxy
+<br><br>
+
+# xywhn2xyxy
+---
+:::ultralytics.yolo.utils.ops.xywhn2xyxy
+<br><br>
+
+# xyxy2xywhn
+---
+:::ultralytics.yolo.utils.ops.xyxy2xywhn
+<br><br>
+
+# xyn2xy
+---
+:::ultralytics.yolo.utils.ops.xyn2xy
+<br><br>
+
+# xywh2ltwh
+---
+:::ultralytics.yolo.utils.ops.xywh2ltwh
+<br><br>
+
+# xyxy2ltwh
+---
+:::ultralytics.yolo.utils.ops.xyxy2ltwh
+<br><br>
+
+# ltwh2xywh
+---
+:::ultralytics.yolo.utils.ops.ltwh2xywh
+<br><br>
+
+# ltwh2xyxy
+---
+:::ultralytics.yolo.utils.ops.ltwh2xyxy
+<br><br>
+
+# segments2boxes
+---
+:::ultralytics.yolo.utils.ops.segments2boxes
+<br><br>
+
+# resample_segments
+---
+:::ultralytics.yolo.utils.ops.resample_segments
+<br><br>
+
+# crop_mask
+---
+:::ultralytics.yolo.utils.ops.crop_mask
+<br><br>
+
+# process_mask_upsample
+---
+:::ultralytics.yolo.utils.ops.process_mask_upsample
+<br><br>
+
+# process_mask
+---
+:::ultralytics.yolo.utils.ops.process_mask
+<br><br>
+
+# process_mask_native
+---
+:::ultralytics.yolo.utils.ops.process_mask_native
+<br><br>
+
+# scale_coords
+---
+:::ultralytics.yolo.utils.ops.scale_coords
+<br><br>
+
+# masks2segments
+---
+:::ultralytics.yolo.utils.ops.masks2segments
+<br><br>
+
+# clean_str
+---
+:::ultralytics.yolo.utils.ops.clean_str
+<br><br>

docs/reference/yolo/utils/plotting.md

@@ -0,0 +1,43 @@
+---
+description: 'Discover the power of YOLO''s plotting functions: Colors, Labels and Images. Code examples to output targets and visualize features. Check it now.'
+---
+
+# Colors
+---
+:::ultralytics.yolo.utils.plotting.Colors
+<br><br>
+
+# Annotator
+---
+:::ultralytics.yolo.utils.plotting.Annotator
+<br><br>
+
+# plot_labels
+---
+:::ultralytics.yolo.utils.plotting.plot_labels
+<br><br>
+
+# save_one_box
+---
+:::ultralytics.yolo.utils.plotting.save_one_box
+<br><br>
+
+# plot_images
+---
+:::ultralytics.yolo.utils.plotting.plot_images
+<br><br>
+
+# plot_results
+---
+:::ultralytics.yolo.utils.plotting.plot_results
+<br><br>
+
+# output_to_target
+---
+:::ultralytics.yolo.utils.plotting.output_to_target
+<br><br>
+
+# feature_visualization
+---
+:::ultralytics.yolo.utils.plotting.feature_visualization
+<br><br>

docs/reference/yolo/utils/tal.md

@@ -0,0 +1,33 @@
+---
+description: Improve your YOLO models with Ultralytics' TaskAlignedAssigner, select_highest_overlaps, and dist2bbox utilities. Streamline your workflow today.
+---
+
+# TaskAlignedAssigner
+---
+:::ultralytics.yolo.utils.tal.TaskAlignedAssigner
+<br><br>
+
+# select_candidates_in_gts
+---
+:::ultralytics.yolo.utils.tal.select_candidates_in_gts
+<br><br>
+
+# select_highest_overlaps
+---
+:::ultralytics.yolo.utils.tal.select_highest_overlaps
+<br><br>
+
+# make_anchors
+---
+:::ultralytics.yolo.utils.tal.make_anchors
+<br><br>
+
+# dist2bbox
+---
+:::ultralytics.yolo.utils.tal.dist2bbox
+<br><br>
+
+# bbox2dist
+---
+:::ultralytics.yolo.utils.tal.bbox2dist
+<br><br>

docs/reference/yolo/utils/torch_utils.md

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+---
+description: Optimize your PyTorch models with Ultralytics YOLO's torch_utils functions such as ModelEMA, select_device, and is_parallel.
+---
+
+# ModelEMA
+---
+:::ultralytics.yolo.utils.torch_utils.ModelEMA
+<br><br>
+
+# EarlyStopping
+---
+:::ultralytics.yolo.utils.torch_utils.EarlyStopping
+<br><br>
+
+# torch_distributed_zero_first
+---
+:::ultralytics.yolo.utils.torch_utils.torch_distributed_zero_first
+<br><br>
+
+# smart_inference_mode
+---
+:::ultralytics.yolo.utils.torch_utils.smart_inference_mode
+<br><br>
+
+# select_device
+---
+:::ultralytics.yolo.utils.torch_utils.select_device
+<br><br>
+
+# time_sync
+---
+:::ultralytics.yolo.utils.torch_utils.time_sync
+<br><br>
+
+# fuse_conv_and_bn
+---
+:::ultralytics.yolo.utils.torch_utils.fuse_conv_and_bn
+<br><br>
+
+# fuse_deconv_and_bn
+---
+:::ultralytics.yolo.utils.torch_utils.fuse_deconv_and_bn
+<br><br>
+
+# model_info
+---
+:::ultralytics.yolo.utils.torch_utils.model_info
+<br><br>
+
+# get_num_params
+---
+:::ultralytics.yolo.utils.torch_utils.get_num_params
+<br><br>
+
+# get_num_gradients
+---
+:::ultralytics.yolo.utils.torch_utils.get_num_gradients
+<br><br>
+
+# get_flops
+---
+:::ultralytics.yolo.utils.torch_utils.get_flops
+<br><br>
+
+# initialize_weights
+---
+:::ultralytics.yolo.utils.torch_utils.initialize_weights
+<br><br>
+
+# scale_img
+---
+:::ultralytics.yolo.utils.torch_utils.scale_img
+<br><br>
+
+# make_divisible
+---
+:::ultralytics.yolo.utils.torch_utils.make_divisible
+<br><br>
+
+# copy_attr
+---
+:::ultralytics.yolo.utils.torch_utils.copy_attr
+<br><br>
+
+# get_latest_opset
+---
+:::ultralytics.yolo.utils.torch_utils.get_latest_opset
+<br><br>
+
+# intersect_dicts
+---
+:::ultralytics.yolo.utils.torch_utils.intersect_dicts
+<br><br>
+
+# is_parallel
+---
+:::ultralytics.yolo.utils.torch_utils.is_parallel
+<br><br>
+
+# de_parallel
+---
+:::ultralytics.yolo.utils.torch_utils.de_parallel
+<br><br>
+
+# one_cycle
+---
+:::ultralytics.yolo.utils.torch_utils.one_cycle
+<br><br>
+
+# init_seeds
+---
+:::ultralytics.yolo.utils.torch_utils.init_seeds
+<br><br>
+
+# strip_optimizer
+---
+:::ultralytics.yolo.utils.torch_utils.strip_optimizer
+<br><br>
+
+# profile
+---
+:::ultralytics.yolo.utils.torch_utils.profile
+<br><br>

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

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+---
+description: Learn how to use ClassificationPredictor in Ultralytics YOLOv8 for object classification tasks in a simple and efficient way.
+---
+
+# ClassificationPredictor
+---
+:::ultralytics.yolo.v8.classify.predict.ClassificationPredictor
+<br><br>
+
+# predict
+---
+:::ultralytics.yolo.v8.classify.predict.predict
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: Train a custom image classification model using Ultralytics YOLOv8 with ClassificationTrainer. Boost accuracy and efficiency today.
+---
+
+# ClassificationTrainer
+---
+:::ultralytics.yolo.v8.classify.train.ClassificationTrainer
+<br><br>
+
+# train
+---
+:::ultralytics.yolo.v8.classify.train.train
+<br><br>

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

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+---
+description: Ensure model classification accuracy with Ultralytics YOLO's ClassificationValidator. Validate and improve your model with ease.
+---
+
+# ClassificationValidator
+---
+:::ultralytics.yolo.v8.classify.val.ClassificationValidator
+<br><br>
+
+# val
+---
+:::ultralytics.yolo.v8.classify.val.val
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: Detect and predict objects in images and videos using the Ultralytics YOLO v8 model with DetectionPredictor.
+---
+
+# DetectionPredictor
+---
+:::ultralytics.yolo.v8.detect.predict.DetectionPredictor
+<br><br>
+
+# predict
+---
+:::ultralytics.yolo.v8.detect.predict.predict
+<br><br>

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

@@ -0,0 +1,18 @@
+---
+description: Train and optimize custom object detection models with Ultralytics DetectionTrainer and train functions. Get started with YOLO v8 today.
+---
+
+# DetectionTrainer
+---
+:::ultralytics.yolo.v8.detect.train.DetectionTrainer
+<br><br>
+
+# Loss
+---
+:::ultralytics.yolo.v8.detect.train.Loss
+<br><br>
+
+# train
+---
+:::ultralytics.yolo.v8.detect.train.train
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: Validate YOLOv5 detections using this PyTorch module. Ensure model accuracy with NMS IOU threshold tuning and label mapping.
+---
+
+# DetectionValidator
+---
+:::ultralytics.yolo.v8.detect.val.DetectionValidator
+<br><br>
+
+# val
+---
+:::ultralytics.yolo.v8.detect.val.val
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: Predict human pose coordinates and confidence scores using YOLOv5. Use on real-time video streams or static images.
+---
+
+# PosePredictor
+---
+:::ultralytics.yolo.v8.pose.predict.PosePredictor
+<br><br>
+
+# predict
+---
+:::ultralytics.yolo.v8.pose.predict.predict
+<br><br>

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

@@ -0,0 +1,18 @@
+---
+description: Boost posture detection using PoseTrainer and train models using train() API. Learn PoseLoss for ultra-fast and accurate pose detection with Ultralytics YOLO.
+---
+
+# PoseTrainer
+---
+:::ultralytics.yolo.v8.pose.train.PoseTrainer
+<br><br>
+
+# PoseLoss
+---
+:::ultralytics.yolo.v8.pose.train.PoseLoss
+<br><br>
+
+# train
+---
+:::ultralytics.yolo.v8.pose.train.train
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: Ensure proper human poses in images with YOLOv8 Pose Validation, part of the Ultralytics YOLO v8 suite.
+---
+
+# PoseValidator
+---
+:::ultralytics.yolo.v8.pose.val.PoseValidator
+<br><br>
+
+# val
+---
+:::ultralytics.yolo.v8.pose.val.val
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: '"Use SegmentationPredictor in YOLOv8 for efficient object detection and segmentation. Explore Ultralytics YOLO Docs for more information."'
+---
+
+# SegmentationPredictor
+---
+:::ultralytics.yolo.v8.segment.predict.SegmentationPredictor
+<br><br>
+
+# predict
+---
+:::ultralytics.yolo.v8.segment.predict.predict
+<br><br>

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

@@ -0,0 +1,18 @@
+---
+description: Learn about SegmentationTrainer and Train in Ultralytics YOLO v8 for efficient object detection models. Improve your training with Ultralytics Docs.
+---
+
+# SegmentationTrainer
+---
+:::ultralytics.yolo.v8.segment.train.SegmentationTrainer
+<br><br>
+
+# SegLoss
+---
+:::ultralytics.yolo.v8.segment.train.SegLoss
+<br><br>
+
+# train
+---
+:::ultralytics.yolo.v8.segment.train.train
+<br><br>

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

@@ -0,0 +1,13 @@
+---
+description: Ensure segmentation quality on large datasets with SegmentationValidator. Review and visualize results with ease. Learn more at Ultralytics Docs.
+---
+
+# SegmentationValidator
+---
+:::ultralytics.yolo.v8.segment.val.SegmentationValidator
+<br><br>
+
+# val
+---
+:::ultralytics.yolo.v8.segment.val.val
+<br><br>