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ultralytics 8.0.228 add training time argument (#7054)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2023-12-20 00:01:20 +01:00 • committed by GitHub
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6
docs/en/guides/instance-segmentation-and-tracking.md
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@ -8,8 +8,9 @@ keywords: Ultralytics, YOLOv8, Instance Segmentation, Object Detection, Object T
## What is Instance Segmentation?
[Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) Instance segmentation involves identifying and outlining individual objects in an image, providing a detailed understanding of spatial distribution. Unlike semantic segmentation, it uniquely labels and precisely delineates each object, crucial for tasks like object detection and medical imaging.
Two Types of instance segmentation by Ultralytics YOLOv8.
[Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) instance segmentation involves identifying and outlining individual objects in an image, providing a detailed understanding of spatial distribution. Unlike semantic segmentation, it uniquely labels and precisely delineates each object, crucial for tasks like object detection and medical imaging.
There are two types of instance segmentation tracking available in the Ultralytics package:
- **Instance Segmentation with Class Objects:** Each class object is assigned a unique color for clear visual separation.
@ -22,7 +23,6 @@ Two Types of instance segmentation by Ultralytics YOLOv8.
| ![Ultralytics Instance Segmentation](https://github.com/RizwanMunawar/ultralytics/assets/62513924/d4ad3499-1f33-4871-8fbc-1be0b2643aa2) | ![Ultralytics Instance Segmentation with Object Tracking](https://github.com/RizwanMunawar/ultralytics/assets/62513924/2e5c38cc-fd5c-4145-9682-fa94ae2010a0) |
| Ultralytics Instance Segmentation 😍 | Ultralytics Instance Segmentation with Object Tracking 🔥 |
!!! Example "Instance Segmentation and Tracking"
=== "Instance Segmentation"

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docs/en/guides/vision-eye.md
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@ -22,12 +22,12 @@ keywords: Ultralytics, YOLOv8, Object Detection, Object Tracking, IDetection, Vi
</p>
## Samples
| VisionEye View | VisionEye View With Object Tracking |
|:------------------------------------------------------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| ![VisionEye View Object Mapping using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/7d593acc-2e37-41b0-ad0e-92b4ffae6647) | ![VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/fcd85952-390f-451e-8fb0-b82e943af89c) |
| VisionEye View Object Mapping using Ultralytics YOLOv8 | VisionEye View Object Mapping with Object Tracking using Ultralytics YOLOv8 |
!!! Example "VisionEye Object Mapping using YOLOv8"
=== "VisionEye Object Mapping"

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docs/en/modes/train.md
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@ -180,6 +180,7 @@ Training settings for YOLO models refer to the various hyperparameters and confi
| `model` | `None` | path to model file, i.e. yolov8n.pt, yolov8n.yaml |
| `data` | `None` | path to data file, i.e. coco128.yaml |
| `epochs` | `100` | number of epochs to train for |
| `time` | `None` | number of hours to train for, overrides epochs if supplied |
| `patience` | `50` | epochs to wait for no observable improvement for early stopping of training |
| `batch` | `16` | number of images per batch (-1 for AutoBatch) |
| `imgsz` | `640` | size of input images as integer |

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docs/en/usage/cfg.md
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@ -88,6 +88,7 @@ The training settings for YOLO models encompass various hyperparameters and conf
| `model` | `None` | path to model file, i.e. yolov8n.pt, yolov8n.yaml |
| `data` | `None` | path to data file, i.e. coco128.yaml |
| `epochs` | `100` | number of epochs to train for |
| `time` | `None` | number of hours to train for, overrides epochs if supplied |
| `patience` | `50` | epochs to wait for no observable improvement for early stopping of training |
| `batch` | `16` | number of images per batch (-1 for AutoBatch) |
| `imgsz` | `640` | size of input images as integer |