yolov10/docs/reference/nn/tasks.md

description	keywords
Learn how to work with Ultralytics YOLO Detection, Segmentation & Classification Models, load weights and parse models in PyTorch.	neural network, deep learning, computer vision, object detection, image segmentation, image classification, model ensemble, PyTorch

BaseModel

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:::ultralytics.nn.tasks.BaseModel

DetectionModel

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:::ultralytics.nn.tasks.DetectionModel

SegmentationModel

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:::ultralytics.nn.tasks.SegmentationModel

PoseModel

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:::ultralytics.nn.tasks.PoseModel

ClassificationModel

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:::ultralytics.nn.tasks.ClassificationModel

RTDETRDetectionModel

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:::ultralytics.nn.tasks.RTDETRDetectionModel

Ensemble

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:::ultralytics.nn.tasks.Ensemble

torch_safe_load

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:::ultralytics.nn.tasks.torch_safe_load

attempt_load_weights

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:::ultralytics.nn.tasks.attempt_load_weights

attempt_load_one_weight

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:::ultralytics.nn.tasks.attempt_load_one_weight

parse_model

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:::ultralytics.nn.tasks.parse_model

yaml_model_load

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:::ultralytics.nn.tasks.yaml_model_load

guess_model_scale

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:::ultralytics.nn.tasks.guess_model_scale

guess_model_task

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:::ultralytics.nn.tasks.guess_model_task