HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

Update docs with YOLOv8 banner (#160)

Browse source 
Co-authored-by: Paula Derrenger <107626595+pderrenger@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher 2023-01-09 15:24:01 +01:00 • committed by GitHub
parent fdf294e4e8
commit 96fbf9ce58
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
12 changed files with 252 additions and 41 deletions
Download patch file Download diff file Expand all files Collapse all files

6
docs/engine.md
View file

@ -10,7 +10,7 @@ More details and source code can be found in [`BaseTrainer` Reference](../refere
## DetectionTrainer
Here's how you can use the YOLOv8 `DetectionTrainer` and customize it.
```python
from Ultrlaytics.yolo.v8 import DetectionTrainer
from ultralytics.yolo.v8 import DetectionTrainer
trainer = DetectionTrainer(overrides={...})
trainer.train()
@ -20,7 +20,7 @@ trained_model = trainer.best # get best model
### Customizing the DetectionTrainer
Let's customize the trainer **to train a custom detection model** that is not supported directly. You can do this by simply overloading the existing the `get_model` functionality:
```python
from Ultrlaytics.yolo.v8 import DetectionTrainer
from ultralytics.yolo.v8 import DetectionTrainer
class CustomTrainer(DetectionTrainer):
def get_model(self, cfg, weights):
@ -36,7 +36,7 @@ You now realize that you need to customize the trainer further to:
Here's how you can do it:
```python
from Ultrlaytics.yolo.v8 import DetectionTrainer
from ultralytics.yolo.v8 import DetectionTrainer
class CustomTrainer(DetectionTrainer):
def get_model(self, cfg, weights):