From 5f9911a44a086d99785a4d6a9e566b5a6a6e2f52 Mon Sep 17 00:00:00 2001 From: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com> Date: Tue, 5 Nov 2024 08:20:48 +0800 Subject: [PATCH] Update `overlap_mask` description. (#17324) Co-authored-by: UltralyticsAssistant --- docs/en/macros/train-args.md | 2 +- ultralytics/cfg/default.yaml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/en/macros/train-args.md b/docs/en/macros/train-args.md index cb72bdeced..ede32f910b 100644 --- a/docs/en/macros/train-args.md +++ b/docs/en/macros/train-args.md @@ -43,7 +43,7 @@ | `kobj` | `2.0` | Weight of the keypoint objectness loss in pose estimation models, balancing detection confidence with pose accuracy. | | `label_smoothing` | `0.0` | Applies label smoothing, softening hard labels to a mix of the target label and a uniform distribution over labels, can improve generalization. | | `nbs` | `64` | Nominal batch size for normalization of loss. | -| `overlap_mask` | `True` | Determines whether segmentation masks should overlap during training, applicable in [instance segmentation](https://www.ultralytics.com/glossary/instance-segmentation) tasks. | +| `overlap_mask` | `True` | Determines whether object masks should be merged into a single mask for training, or kept separate for each object. In case of overlap, the smaller mask is overlayed on top of the larger mask during merge. | | `mask_ratio` | `4` | Downsample ratio for segmentation masks, affecting the resolution of masks used during training. | | `dropout` | `0.0` | Dropout rate for regularization in classification tasks, preventing overfitting by randomly omitting units during training. | | `val` | `True` | Enables validation during training, allowing for periodic evaluation of model performance on a separate dataset. | diff --git a/ultralytics/cfg/default.yaml b/ultralytics/cfg/default.yaml index 7922f63592..2ef1f4284f 100644 --- a/ultralytics/cfg/default.yaml +++ b/ultralytics/cfg/default.yaml @@ -36,7 +36,7 @@ profile: False # (bool) profile ONNX and TensorRT speeds during training for log freeze: None # (int | list, optional) freeze first n layers, or freeze list of layer indices during training multi_scale: False # (bool) Whether to use multiscale during training # Segmentation -overlap_mask: True # (bool) masks should overlap during training (segment train only) +overlap_mask: True # (bool) merge object masks into a single image mask during training (segment train only) mask_ratio: 4 # (int) mask downsample ratio (segment train only) # Classification dropout: 0.0 # (float) use dropout regularization (classify train only)