ultralytics 8.0.72 faster Windows trainings and corrupt cache fix (ultralytics#1912)

Co-authored-by: andreaswimmer <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: 3 people

.github/workflows/greetings.yml

@@ -30,7 +30,7 @@ jobs:
 
             If this is a 🐛 Bug Report, please provide a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us debug it.
 
-            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results).
+            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://docs.ultralytics.com/yolov5/tips_for_best_training_results/).
 
             ## Install
 

README.md

@@ -181,14 +181,14 @@ See [Classification Docs](https://docs.ultralytics.com/tasks/classify/) for usag
 
 See [Pose Docs](https://docs.ultralytics.com/tasks/) for usage examples with these models.
 
-| Model                                                                                                | size<br><sup>(pixels) | mAP<sup>box<br>50-95 | mAP<sup>pose<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
-| ---------------------------------------------------------------------------------------------------- | --------------------- | -------------------- | --------------------- | ------------------------------ | ----------------------------------- | ------------------ | ----------------- |
-| [YOLOv8n-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | -                    | 49.7                  | 131.8                          | 1.18                                | 3.3                | 9.2               |
-| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | -                    | 59.2                  | 233.2                          | 1.42                                | 11.6               | 30.2              |
-| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | -                    | 63.6                  | 456.3                          | 2.00                                | 26.4               | 81.0              |
-| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | -                    | 67.0                  | 784.5                          | 2.59                                | 44.4               | 168.6             |
-| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | -                    | 68.9                  | 1607.1                         | 3.73                                | 69.4               | 263.2             |
-| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | -                    | 71.5                  | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
+| Model                                                                                                | size<br><sup>(pixels) | mAP<sup>pose<br>50-95 | mAP<sup>pose<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-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8n-pose.pt)       | 640                   | 49.7                  | 79.7               | 131.8                          | 1.18                                | 3.3                | 9.2               |
+| [YOLOv8s-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8s-pose.pt)       | 640                   | 59.2                  | 85.8               | 233.2                          | 1.42                                | 11.6               | 30.2              |
+| [YOLOv8m-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-pose.pt)       | 640                   | 63.6                  | 88.8               | 456.3                          | 2.00                                | 26.4               | 81.0              |
+| [YOLOv8l-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8l-pose.pt)       | 640                   | 67.0                  | 89.9               | 784.5                          | 2.59                                | 44.4               | 168.6             |
+| [YOLOv8x-pose](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose.pt)       | 640                   | 68.9                  | 90.4               | 1607.1                         | 3.73                                | 69.4               | 263.2             |
+| [YOLOv8x-pose-p6](https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8x-pose-p6.pt) | 1280                  | 71.5                  | 91.3               | 4088.7                         | 10.04                               | 99.1               | 1066.4            |
 
 - **mAP<sup>val</sup>** values are for single-model single-scale on [COCO Keypoints val2017](http://cocodataset.org)
   dataset.