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

Update YOLO11 Actions and Docs (#16596)

Browse source 
Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Ultralytics Assistant 2024-10-01 16:58:12 +02:00 • committed by GitHub
parent 51e93d6111
commit 97f38409fb
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
124 changed files with 1948 additions and 1948 deletions
Download patch file Download diff file Expand all files Collapse all files

12
docs/en/datasets/classify/fashion-mnist.md
View file

@ -16,7 +16,7 @@ The [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist) dataset is
allowfullscreen>
</iframe>
<br>
<strong>Watch:</strong> How to do <a href="https://www.ultralytics.com/glossary/image-classification">Image Classification</a> on Fashion MNIST Dataset using Ultralytics YOLOv8
<strong>Watch:</strong> How to do <a href="https://www.ultralytics.com/glossary/image-classification">Image Classification</a> on Fashion MNIST Dataset using Ultralytics YOLO11
</p>
## Key Features
@ -64,7 +64,7 @@ To train a CNN model on the Fashion-MNIST dataset for 100 [epochs](https://www.u
from ultralytics import YOLO
# Load a model
model = YOLO("yolov8n-cls.pt") # load a pretrained model (recommended for training)
model = YOLO("yolo11n-cls.pt") # load a pretrained model (recommended for training)
# Train the model
results = model.train(data="fashion-mnist", epochs=100, imgsz=28)
@ -74,7 +74,7 @@ To train a CNN model on the Fashion-MNIST dataset for 100 [epochs](https://www.u
```bash
# Start training from a pretrained *.pt model
yolo classify train data=fashion-mnist model=yolov8n-cls.pt epochs=100 imgsz=28
yolo classify train data=fashion-mnist model=yolo11n-cls.pt epochs=100 imgsz=28
```
## Sample Images and Annotations
@ -107,7 +107,7 @@ To train an Ultralytics YOLO model on the Fashion-MNIST dataset, you can use bot
from ultralytics import YOLO
# Load a pretrained model
model = YOLO("yolov8n-cls.pt")
model = YOLO("yolo11n-cls.pt")
# Train the model on Fashion-MNIST
results = model.train(data="fashion-mnist", epochs=100, imgsz=28)
@ -117,7 +117,7 @@ To train an Ultralytics YOLO model on the Fashion-MNIST dataset, you can use bot
=== "CLI"
```bash
yolo classify train data=fashion-mnist model=yolov8n-cls.pt epochs=100 imgsz=28
yolo classify train data=fashion-mnist model=yolo11n-cls.pt epochs=100 imgsz=28
```
For more detailed training parameters, refer to the [Training page](../../modes/train.md).
@ -128,7 +128,7 @@ The [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist) dataset is
### Can I use Ultralytics YOLO for image classification tasks like Fashion-MNIST?
Yes, Ultralytics YOLO models can be used for image classification tasks, including those involving the Fashion-MNIST dataset. YOLOv8, for example, supports various vision tasks such as detection, segmentation, and classification. To get started with image classification tasks, refer to the [Classification page](https://docs.ultralytics.com/tasks/classify/).
Yes, Ultralytics YOLO models can be used for image classification tasks, including those involving the Fashion-MNIST dataset. YOLO11, for example, supports various vision tasks such as detection, segmentation, and classification. To get started with image classification tasks, refer to the [Classification page](https://docs.ultralytics.com/tasks/classify/).
### What are the key features and structure of the Fashion-MNIST dataset?