Reference for ultralytics/engine/validator.py
Note
Full source code for this file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/engine/validator.py. Help us fix any issues you see by submitting a Pull Request 🛠️. Thank you 🙏!
ultralytics.engine.validator.BaseValidator
BaseValidator
A base class for creating validators.
Attributes:
Name | Type | Description |
---|---|---|
args |
SimpleNamespace
|
Configuration for the validator. |
dataloader |
DataLoader
|
Dataloader to use for validation. |
pbar |
tqdm
|
Progress bar to update during validation. |
model |
Module
|
Model to validate. |
data |
dict
|
Data dictionary. |
device |
device
|
Device to use for validation. |
batch_i |
int
|
Current batch index. |
training |
bool
|
Whether the model is in training mode. |
names |
dict
|
Class names. |
seen |
Records the number of images seen so far during validation. |
|
stats |
Placeholder for statistics during validation. |
|
confusion_matrix |
Placeholder for a confusion matrix. |
|
nc |
Number of classes. |
|
iouv |
(torch.Tensor): IoU thresholds from 0.50 to 0.95 in spaces of 0.05. |
|
jdict |
dict
|
Dictionary to store JSON validation results. |
speed |
dict
|
Dictionary with keys 'preprocess', 'inference', 'loss', 'postprocess' and their respective batch processing times in milliseconds. |
save_dir |
Path
|
Directory to save results. |
plots |
dict
|
Dictionary to store plots for visualization. |
callbacks |
dict
|
Dictionary to store various callback functions. |
Source code in ultralytics/engine/validator.py
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|
metric_keys
property
Returns the metric keys used in YOLO training/validation.
__call__(trainer=None, model=None)
Supports validation of a pre-trained model if passed or a model being trained if trainer is passed (trainer gets priority).
Source code in ultralytics/engine/validator.py
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__init__(dataloader=None, save_dir=None, pbar=None, args=None, _callbacks=None)
Initializes a BaseValidator instance.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
dataloader |
DataLoader
|
Dataloader to be used for validation. |
None
|
save_dir |
Path
|
Directory to save results. |
None
|
pbar |
tqdm
|
Progress bar for displaying progress. |
None
|
args |
SimpleNamespace
|
Configuration for the validator. |
None
|
_callbacks |
dict
|
Dictionary to store various callback functions. |
None
|
Source code in ultralytics/engine/validator.py
add_callback(event, callback)
build_dataset(img_path)
check_stats(stats)
eval_json(stats)
finalize_metrics(*args, **kwargs)
get_dataloader(dataset_path, batch_size)
Get data loader from dataset path and batch size.
get_desc()
get_stats()
init_metrics(model)
match_predictions(pred_classes, true_classes, iou, use_scipy=False)
Matches predictions to ground truth objects (pred_classes, true_classes) using IoU.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
pred_classes |
Tensor
|
Predicted class indices of shape(N,). |
required |
true_classes |
Tensor
|
Target class indices of shape(M,). |
required |
iou |
Tensor
|
An NxM tensor containing the pairwise IoU values for predictions and ground of truth |
required |
use_scipy |
bool
|
Whether to use scipy for matching (more precise). |
False
|
Returns:
Type | Description |
---|---|
Tensor
|
Correct tensor of shape(N,10) for 10 IoU thresholds. |