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ultralytics 8.0.65 YOLOv8 Pose models (#1347)

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This commit is contained in:
Ayush Chaurasia
2023-04-06 03:55:32 +05:30
committed by GitHub
parent 9af3e69b1a
commit 1cb92d7f42
57 changed files with 1578 additions and 489 deletions
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2
docs/usage/cfg.md
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@ -110,6 +110,8 @@ The training settings for YOLO models encompass various hyperparameters and conf
| `box` | `7.5` | box loss gain |
| `cls` | `0.5` | cls loss gain (scale with pixels) |
| `dfl` | `1.5` | dfl loss gain |
| `pose` | `12.0` | pose loss gain (pose-only) |
| `kobj` | `2.0` | keypoint obj loss gain (pose-only) |
| `fl_gamma` | `0.0` | focal loss gamma (efficientDet default gamma=1.5) |
| `label_smoothing` | `0.0` | label smoothing (fraction) |
| `nbs` | `64` | nominal batch size |

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docs/usage/engine.md
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@ -74,7 +74,7 @@ trainer.add_callback("on_train_epoch_end", log_model) # Adds to existing callba
trainer.train()
```
To know more about Callback triggering events and entry point, checkout our Callbacks guide # TODO
To know more about Callback triggering events and entry point, checkout our [Callbacks Guide](callbacks.md)
## Other engine components

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docs/usage/python.md
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@ -59,7 +59,6 @@ accurately predict the classes and locations of objects in an image.
=== "Resume"
```python
# TODO: Resume feature is under development and should be released soon.
model = YOLO("last.pt")
model.train(resume=True)
```