yolov8_test/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

---

::: ultralytics.nn.tasks.BaseModel

DetectionModel

---

::: ultralytics.nn.tasks.DetectionModel

SegmentationModel

---

::: ultralytics.nn.tasks.SegmentationModel

PoseModel

---

::: ultralytics.nn.tasks.PoseModel

ClassificationModel

---

::: ultralytics.nn.tasks.ClassificationModel

RTDETRDetectionModel

---

::: ultralytics.nn.tasks.RTDETRDetectionModel

Ensemble

---

::: ultralytics.nn.tasks.Ensemble

torch_safe_load

---

::: ultralytics.nn.tasks.torch_safe_load

attempt_load_weights

---

::: ultralytics.nn.tasks.attempt_load_weights

attempt_load_one_weight

---

::: ultralytics.nn.tasks.attempt_load_one_weight

parse_model

---

::: ultralytics.nn.tasks.parse_model

yaml_model_load

---

::: ultralytics.nn.tasks.yaml_model_load

guess_model_scale

---

::: ultralytics.nn.tasks.guess_model_scale

guess_model_task

---

::: ultralytics.nn.tasks.guess_model_task