--- comments: true description: Learn how to utilize callbacks in the Ultralytics framework during train, val, export, and predict modes for enhanced functionality. keywords: Ultralytics, YOLO, callbacks guide, training callback, validation callback, export callback, prediction callback --- ## 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.



Watch: Mastering Ultralytics YOLOv8: Callbacks

## 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 from ultralytics import YOLO def on_predict_batch_end(predictor): # Retrieve the batch data _, image, _, _ = predictor.batch # Ensure that image is a list image = image if isinstance(image, list) else [image] # Combine the prediction results with the corresponding frames predictor.results = zip(predictor.results, image) # Create a YOLO model instance model = YOLO(f'yolov8n.pt') # Add the custom callback to the model model.add_callback("on_predict_batch_end", on_predict_batch_end) # Iterate through the results and frames for (result, frame) in model.predict(): # or model.track() pass ``` ## All callbacks Here are all supported callbacks. See callbacks [source code](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/callbacks/base.py) for additional details. ### Trainer Callbacks | Callback | Description | |-----------------------------|---------------------------------------------------------| | `on_pretrain_routine_start` | Triggered at the beginning of pre-training routine | | `on_pretrain_routine_end` | Triggered at the end of pre-training routine | | `on_train_start` | Triggered when the training starts | | `on_train_epoch_start` | Triggered at the start of each training epoch | | `on_train_batch_start` | Triggered at the start of each training batch | | `optimizer_step` | Triggered during the optimizer step | | `on_before_zero_grad` | Triggered before gradients are zeroed | | `on_train_batch_end` | Triggered at the end of each training batch | | `on_train_epoch_end` | Triggered at the end of each training epoch | | `on_fit_epoch_end` | Triggered at the end of each fit epoch | | `on_model_save` | Triggered when the model is saved | | `on_train_end` | Triggered when the training process ends | | `on_params_update` | Triggered when model parameters are updated | | `teardown` | Triggered when the training process is being cleaned up | ### Validator Callbacks | Callback | Description | |----------------------|-------------------------------------------------| | `on_val_start` | Triggered when the validation starts | | `on_val_batch_start` | Triggered at the start of each validation batch | | `on_val_batch_end` | Triggered at the end of each validation batch | | `on_val_end` | Triggered when the validation ends | ### Predictor Callbacks | Callback | Description | |------------------------------|---------------------------------------------------| | `on_predict_start` | Triggered when the prediction process starts | | `on_predict_batch_start` | Triggered at the start of each prediction batch | | `on_predict_postprocess_end` | Triggered at the end of prediction postprocessing | | `on_predict_batch_end` | Triggered at the end of each prediction batch | | `on_predict_end` | Triggered when the prediction process ends | ### Exporter Callbacks | Callback | Description | |-------------------|------------------------------------------| | `on_export_start` | Triggered when the export process starts | | `on_export_end` | Triggered when the export process ends |