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ultralytics 8.0.229 add model.embed() method (#7098)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2023-12-22 15:32:06 +01:00 • committed by GitHub
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11 changed files with 65 additions and 14 deletions
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3
docs/en/guides/workouts-monitoring.md
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@ -125,5 +125,6 @@ Monitoring workouts through pose estimation with [Ultralytics YOLOv8](https://gi
| `visualize` | `bool` | `False` | visualize model features |
| `augment` | `bool` | `False` | apply image augmentation to prediction sources |
| `agnostic_nms` | `bool` | `False` | class-agnostic NMS |
| `classes` | `list[int]` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `retina_masks` | `bool` | `False` | use high-resolution segmentation masks |
| `classes` | `None or list` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `embed` | `list[int]` | `None` | return feature vectors/embeddings from given layers |

3
docs/en/modes/predict.md
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@ -355,8 +355,9 @@ Inference arguments:
| `visualize` | `bool` | `False` | visualize model features |
| `augment` | `bool` | `False` | apply image augmentation to prediction sources |
| `agnostic_nms` | `bool` | `False` | class-agnostic NMS |
| `classes` | `list[int]` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `retina_masks` | `bool` | `False` | use high-resolution segmentation masks |
| `classes` | `None or list` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `embed` | `list[int]` | `None` | return feature vectors/embeddings from given layers |
Visualization arguments:

4
docs/en/reference/nn/autobackend.md
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@ -18,3 +18,7 @@ keywords: Ultralytics, AutoBackend, check_class_names, YOLO, YOLO models, optimi
## ::: ultralytics.nn.autobackend.check_class_names
<br><br>
## ::: ultralytics.nn.autobackend.default_class_names
<br><br>

3
docs/en/usage/cfg.md
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@ -156,8 +156,9 @@ Inference arguments:
| `visualize` | `bool` | `False` | visualize model features |
| `augment` | `bool` | `False` | apply image augmentation to prediction sources |
| `agnostic_nms` | `bool` | `False` | class-agnostic NMS |
| `classes` | `list[int]` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `retina_masks` | `bool` | `False` | use high-resolution segmentation masks |
| `classes` | `None or list` | `None` | filter results by class, i.e. classes=0, or classes=[0,2,3] |
| `embed` | `list[int]` | `None` | return feature vectors/embeddings from given layers |
Visualization arguments: