mirror of
https://github.com/THU-MIG/yolov10.git
synced 2025-05-23 21:44:22 +08:00
f921e1ac21
Co-authored-by: Richard Aljaste <richardaljasteabramson@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Vuong Kha Sieu <75152429+hotfur@users.noreply.github.com>
87 lines
1.5 KiB
Markdown
87 lines
1.5 KiB
Markdown
## Callbacks
|
|
|
|
Ultralytics framework supports callbacks as entry points in strategic stages of train, val, export, and predict modes.
|
|
Each callback accepts a `Trainer`, `Validator`, or `Predictor` object depending on the operation type. All properties of
|
|
these objects can be found in Reference section of the docs.
|
|
|
|
## Examples
|
|
|
|
### Returning additional information with Prediction
|
|
|
|
In this example, we want to return the original frame with each result object. Here's how we can do that
|
|
|
|
```python
|
|
def on_predict_batch_end(predictor):
|
|
# results -> List[batch_size]
|
|
_, _, im0s, _, _ = predictor.batch
|
|
im0s = im0s if isinstance(im0s, list) else [im0s]
|
|
predictor.results = zip(predictor.results, im0s)
|
|
|
|
model = YOLO(f"yolov8n.pt")
|
|
model.add_callback("on_predict_batch_end", on_predict_batch_end)
|
|
for (result, frame) in model.track/predict():
|
|
pass
|
|
```
|
|
|
|
## All callbacks
|
|
|
|
Here are all supported callbacks.
|
|
|
|
### Trainer
|
|
|
|
`on_pretrain_routine_start`
|
|
|
|
`on_pretrain_routine_end`
|
|
|
|
`on_train_start`
|
|
|
|
`on_train_epoch_start`
|
|
|
|
`on_train_batch_start`
|
|
|
|
`optimizer_step`
|
|
|
|
`on_before_zero_grad`
|
|
|
|
`on_train_batch_end`
|
|
|
|
`on_train_epoch_end`
|
|
|
|
`on_fit_epoch_end`
|
|
|
|
`on_model_save`
|
|
|
|
`on_train_end`
|
|
|
|
`on_params_update`
|
|
|
|
`teardown`
|
|
|
|
### Validator
|
|
|
|
`on_val_start`
|
|
|
|
`on_val_batch_start`
|
|
|
|
`on_val_batch_end`
|
|
|
|
`on_val_end`
|
|
|
|
### Predictor
|
|
|
|
`on_predict_start`
|
|
|
|
`on_predict_batch_start`
|
|
|
|
`on_predict_postprocess_end`
|
|
|
|
`on_predict_batch_end`
|
|
|
|
`on_predict_end`
|
|
|
|
### Exporter
|
|
|
|
`on_export_start`
|
|
|
|
`on_export_end`
|