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92 lines
2.7 KiB
92 lines
2.7 KiB
## Using YOLO models
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This is the simplest way of simply using yolo models in a python environment. It can be imported from the `ultralytics` module.
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!!! example "Usage"
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=== "Training"
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```python
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from ultralytics import YOLO
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model = YOLO("yolov8n.yaml")
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model(img_tensor) # Or model.forward(). inference.
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model.train(data="coco128.yaml", epochs=5)
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```
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=== "Training pretrained"
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```python
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from ultralytics import YOLO
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model = YOLO("yolov8n.pt") # pass any model type
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model(...) # inference
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model.train(epochs=5)
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```
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=== "Resume Training"
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```python
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from ultralytics import YOLO
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model = YOLO()
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model.resume(task="detect") # resume last detection training
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model.resume(model="last.pt") # resume from a given model/run
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```
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=== "Visualize/save Predictions"
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```python
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from ultralytics import YOLO
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model = YOLO("model.pt")
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model.predict(source="0") # accepts all formats - img/folder/vid.*(mp4/format). 0 for webcam
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model.predict(source="folder", view_img=True) # Display preds. Accepts all yolo predict arguments
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```
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!!! note "Export and Deployment"
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=== "Export, Fuse & info"
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```python
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from ultralytics import YOLO
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model = YOLO("model.pt")
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model.fuse()
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model.info(verbose=True) # Print model information
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model.export(format=) # TODO:
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```
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=== "Deployment"
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More functionality coming soon
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To know more about using `YOLO` models, refer Model class Reference
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[Model reference](reference/model.md){ .md-button .md-button--primary}
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---
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### Using Trainers
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`YOLO` model class is a high-level wrapper on the Trainer classes. Each YOLO task has its own trainer that inherits from `BaseTrainer`.
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!!! tip "Detection Trainer Example"
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```python
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from ultralytics.yolo import v8 import DetectionTrainer, DetectionValidator, DetectionPredictor
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# trainer
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trainer = DetectionTrainer(overrides={})
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trainer.train()
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trained_model = trainer.best
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# Validator
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val = DetectionValidator(args=...)
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val(model=trained_model)
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# predictor
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pred = DetectionPredictor(overrides={})
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pred(source=SOURCE, model=trained_model)
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# resume from last weight
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overrides["resume"] = trainer.last
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trainer = detect.DetectionTrainer(overrides=overrides)
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```
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You can easily customize Trainers to support custom tasks or explore R&D ideas.
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Learn more about Customizing `Trainers`, `Validators` and `Predictors` to suit your project needs in the Customization Section.
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[Customization tutorials](engine.md){ .md-button .md-button--primary}
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