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ultralytics 8.0.235 YOLOv8 OBB train, val, predict and export (#4499)

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@ -175,6 +175,25 @@ See [Pose Docs](https://docs.ultralytics.com/tasks/pose/) for usage examples wit
</details>
<details><summary>Obb (DOTAv1)</summary>
See [Obb Docs](https://docs.ultralytics.com/tasks/obb/) for usage examples with these models trained on [DOTAv1](https://docs.ultralytics.com/datasets/obb/dota-v1), which include 15 pre-trained classes.
| Model | size<br><sup>(pixels) | mAP<sup>box<br>50 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
| -------------------------------------------------------------------------------------------- | --------------------- | ----------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
| [YOLOv8n-obb](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-obb.pt) | 1024 | \<++> | \<++> | \<++> | 3.2 | 23.3 |
| [YOLOv8s-obb](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-obb.pt) | 1024 | \<++> | \<++> | \<++> | 11.4 | 76.3 |
| [YOLOv8m-obb](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-obb.pt) | 1024 | \<++> | \<++> | \<++> | 26.4 | 208.6 |
| [YOLOv8l-obb](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-obb.pt) | 1024 | \<++> | \<++> | \<++> | 44.5 | 433.8 |
| [YOLOv8x-obb](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-obb.pt) | 1024 | \<++> | \<++> | \<++> | 69.5 | 676.7 |
<!-- TODO: should we report multi-scale results only as they're better or both multi-scale and single-scale. -->
- **mAP<sup>val</sup>** values are for single-model single-scale on [DOTAv1](https://captain-whu.github.io/DOTA/index.html) dataset. <br>Reproduce by `yolo val obb data=DOTAv1.yaml device=0`
- **Speed** averaged over DOTAv1 val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. <br>Reproduce by `yolo val obb data=DOTAv1.yaml batch=1 device=0|cpu`
</details>
<details><summary>Classification (ImageNet)</summary>
See [Classification Docs](https://docs.ultralytics.com/tasks/classify/) for usage examples with these models trained on [ImageNet](https://docs.ultralytics.com/datasets/classify/imagenet/), which include 1000 pretrained classes.