Reference for ultralytics/utils/loss.py
Note
Full source code for this file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/utils/loss.py. Help us fix any issues you see by submitting a Pull Request 🛠️. Thank you 🙏!
ultralytics.utils.loss.VarifocalLoss
Bases: Module
Varifocal loss by Zhang et al. https://arxiv.org/abs/2008.13367.
Source code in ultralytics/utils/loss.py
__init__()
forward(pred_score, gt_score, label, alpha=0.75, gamma=2.0)
staticmethod
Computes varfocal loss.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.FocalLoss
Bases: Module
Wraps focal loss around existing loss_fcn(), i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=1.5).
Source code in ultralytics/utils/loss.py
forward(pred, label, gamma=1.5, alpha=0.25)
staticmethod
Calculates and updates confusion matrix for object detection/classification tasks.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.BboxLoss
Bases: Module
Source code in ultralytics/utils/loss.py
__init__(reg_max, use_dfl=False)
Initialize the BboxLoss module with regularization maximum and DFL settings.
forward(pred_dist, pred_bboxes, anchor_points, target_bboxes, target_scores, target_scores_sum, fg_mask)
IoU loss.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.KeypointLoss
Bases: Module
Criterion class for computing training losses.
Source code in ultralytics/utils/loss.py
forward(pred_kpts, gt_kpts, kpt_mask, area)
Calculates keypoint loss factor and Euclidean distance loss for predicted and actual keypoints.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.v8DetectionLoss
Criterion class for computing training losses.
Source code in ultralytics/utils/loss.py
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__call__(preds, batch)
Calculate the sum of the loss for box, cls and dfl multiplied by batch size.
Source code in ultralytics/utils/loss.py
bbox_decode(anchor_points, pred_dist)
Decode predicted object bounding box coordinates from anchor points and distribution.
Source code in ultralytics/utils/loss.py
preprocess(targets, batch_size, scale_tensor)
Preprocesses the target counts and matches with the input batch size to output a tensor.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.v8SegmentationLoss
Bases: v8DetectionLoss
Criterion class for computing training losses.
Source code in ultralytics/utils/loss.py
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__call__(preds, batch)
Calculate and return the loss for the YOLO model.
Source code in ultralytics/utils/loss.py
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single_mask_loss(gt_mask, pred, proto, xyxy, area)
Mask loss for one image.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.v8PoseLoss
Bases: v8DetectionLoss
Criterion class for computing training losses.
Source code in ultralytics/utils/loss.py
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__call__(preds, batch)
Calculate the total loss and detach it.
Source code in ultralytics/utils/loss.py
kpts_decode(anchor_points, pred_kpts)
staticmethod
Decodes predicted keypoints to image coordinates.
Source code in ultralytics/utils/loss.py
ultralytics.utils.loss.v8ClassificationLoss
Criterion class for computing training losses.
Source code in ultralytics/utils/loss.py
__call__(preds, batch)
Compute the classification loss between predictions and true labels.