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Update coco-seg.yaml to coco.yaml (#17739)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Mohammed Yasin 2024-11-25 00:05:51 +08:00 • committed by GitHub
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4
README.md
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@ -150,8 +150,8 @@ See [Segmentation Docs](https://docs.ultralytics.com/tasks/segment/) for usage e
| [YOLO11l-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11l-seg.pt) | 640 | 53.4 | 42.9 | 344.2 ± 3.2 | 7.8 ± 0.2 | 27.6 | 142.2 |
| [YOLO11x-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11x-seg.pt) | 640 | 54.7 | 43.8 | 664.5 ± 3.2 | 15.8 ± 0.7 | 62.1 | 319.0 |
- **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](https://cocodataset.org/) dataset. <br>Reproduce by `yolo val segment data=coco-seg.yaml device=0`
- **Speed** averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. <br>Reproduce by `yolo val segment data=coco-seg.yaml batch=1 device=0|cpu`
- **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](https://cocodataset.org/) dataset. <br>Reproduce by `yolo val segment data=coco.yaml device=0`
- **Speed** averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. <br>Reproduce by `yolo val segment data=coco.yaml batch=1 device=0|cpu`
</details>

4
README.zh-CN.md
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@ -150,8 +150,8 @@ YOLO11 [检测](https://docs.ultralytics.com/tasks/detect/)、[分割](https://d
| [YOLO11l-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11l-seg.pt) | 640 | 53.4 | 42.9 | 344.2 ± 3.2 | 7.8 ± 0.2 | 27.6 | 142.2 |
| [YOLO11x-seg](https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11x-seg.pt) | 640 | 54.7 | 43.8 | 664.5 ± 3.2 | 15.8 ± 0.7 | 62.1 | 319.0 |
- **mAP<sup>val</sup>** 值针对单模型单尺度在 [COCO val2017](https://cocodataset.org/) 数据集上进行。 <br>复制命令 `yolo val segment data=coco-seg.yaml device=0`
- **速度**在使用 [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) 实例的 COCO 验证图像上平均。 <br>复制命令 `yolo val segment data=coco-seg.yaml batch=1 device=0|cpu`
- **mAP<sup>val</sup>** 值针对单模型单尺度在 [COCO val2017](https://cocodataset.org/) 数据集上进行。 <br>复制命令 `yolo val segment data=coco.yaml device=0`
- **速度**在使用 [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) 实例的 COCO 验证图像上平均。 <br>复制命令 `yolo val segment data=coco.yaml batch=1 device=0|cpu`
</details>

8
docs/en/datasets/segment/coco.md
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@ -56,14 +56,14 @@ To train a YOLO11n-seg model on the COCO-Seg dataset for 100 [epochs](https://ww
model = YOLO("yolo11n-seg.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="coco-seg.yaml", epochs=100, imgsz=640)
results = model.train(data="coco.yaml", epochs=100, imgsz=640)
```
=== "CLI"
```bash
# Start training from a pretrained *.pt model
yolo segment train data=coco-seg.yaml model=yolo11n-seg.pt epochs=100 imgsz=640
yolo segment train data=coco.yaml model=yolo11n-seg.pt epochs=100 imgsz=640
```
## Sample Images and Annotations
@ -118,14 +118,14 @@ To train a YOLO11n-seg model on the COCO-Seg dataset for 100 epochs with an imag
model = YOLO("yolo11n-seg.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="coco-seg.yaml", epochs=100, imgsz=640)
results = model.train(data="coco.yaml", epochs=100, imgsz=640)
```
=== "CLI"
```bash
# Start training from a pretrained *.pt model
yolo segment train data=coco-seg.yaml model=yolo11n-seg.pt epochs=100 imgsz=640
yolo segment train data=coco.yaml model=yolo11n-seg.pt epochs=100 imgsz=640
```
### What are the key features of the COCO-Seg dataset?

4
docs/en/tasks/segment.md
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@ -36,8 +36,8 @@ YOLO11 pretrained Segment models are shown here. Detect, Segment and Pose models
{% include "macros/yolo-seg-perf.md" %}
- **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](https://cocodataset.org/) dataset. <br>Reproduce by `yolo val segment data=coco-seg.yaml device=0`
- **Speed** averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. <br>Reproduce by `yolo val segment data=coco-seg.yaml batch=1 device=0|cpu`
- **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](https://cocodataset.org/) dataset. <br>Reproduce by `yolo val segment data=coco.yaml device=0`
- **Speed** averaged over COCO val images using an [Amazon EC2 P4d](https://aws.amazon.com/ec2/instance-types/p4/) instance. <br>Reproduce by `yolo val segment data=coco.yaml batch=1 device=0|cpu`
## Train