From 9ff33d67b6aba970cb675ba9e219ae75907d109f Mon Sep 17 00:00:00 2001 From: Jan Knobloch <116908874+jk4e@users.noreply.github.com> Date: Thu, 1 Aug 2024 17:18:31 +0200 Subject: [PATCH] Fix incorrect CLI commands in Datasets Docs (#14889) --- docs/en/datasets/classify/caltech101.md | 4 ++-- docs/en/datasets/classify/caltech256.md | 4 ++-- docs/en/datasets/classify/cifar10.md | 4 ++-- docs/en/datasets/classify/cifar100.md | 4 ++-- docs/en/datasets/classify/fashion-mnist.md | 4 ++-- docs/en/datasets/classify/imagenet.md | 4 ++-- docs/en/datasets/classify/imagenet10.md | 4 ++-- docs/en/datasets/classify/imagenette.md | 8 ++++---- docs/en/datasets/classify/imagewoof.md | 4 ++-- docs/en/datasets/classify/mnist.md | 4 ++-- docs/en/datasets/obb/index.md | 4 ++-- docs/en/datasets/pose/coco.md | 4 ++-- docs/en/datasets/pose/coco8-pose.md | 4 ++-- docs/en/datasets/pose/index.md | 2 +- docs/en/datasets/segment/coco.md | 4 ++-- docs/en/datasets/segment/coco8-seg.md | 4 ++-- docs/en/datasets/segment/index.md | 2 +- 17 files changed, 34 insertions(+), 34 deletions(-) diff --git a/docs/en/datasets/classify/caltech101.md b/docs/en/datasets/classify/caltech101.md index 451c4cc9..6a75f66a 100644 --- a/docs/en/datasets/classify/caltech101.md +++ b/docs/en/datasets/classify/caltech101.md @@ -46,7 +46,7 @@ To train a YOLO model on the Caltech-101 dataset for 100 epochs, you can use the ```bash # Start training from a pretrained *.pt model - yolo detect train data=caltech101 model=yolov8n-cls.pt epochs=100 imgsz=416 + yolo classify train data=caltech101 model=yolov8n-cls.pt epochs=100 imgsz=416 ``` ## Sample Images and Annotations @@ -108,7 +108,7 @@ To train an Ultralytics YOLO model on the Caltech-101 dataset, you can use the p ```bash # Start training from a pretrained *.pt model - yolo detect train data=caltech101 model=yolov8n-cls.pt epochs=100 imgsz=416 + yolo classify train data=caltech101 model=yolov8n-cls.pt epochs=100 imgsz=416 ``` For more detailed arguments and options, refer to the model [Training](../../modes/train.md) page. diff --git a/docs/en/datasets/classify/caltech256.md b/docs/en/datasets/classify/caltech256.md index 6c6cf4a6..c7b367cc 100644 --- a/docs/en/datasets/classify/caltech256.md +++ b/docs/en/datasets/classify/caltech256.md @@ -57,7 +57,7 @@ To train a YOLO model on the Caltech-256 dataset for 100 epochs, you can use the ```bash # Start training from a pretrained *.pt model - yolo detect train data=caltech256 model=yolov8n-cls.pt epochs=100 imgsz=416 + yolo classify train data=caltech256 model=yolov8n-cls.pt epochs=100 imgsz=416 ``` ## Sample Images and Annotations @@ -116,7 +116,7 @@ To train a YOLO model on the Caltech-256 dataset for 100 epochs, you can use the ```bash # Start training from a pretrained *.pt model - yolo detect train data=caltech256 model=yolov8n-cls.pt epochs=100 imgsz=416 + yolo classify train data=caltech256 model=yolov8n-cls.pt epochs=100 imgsz=416 ``` ### What are the most common use cases for the Caltech-256 dataset? diff --git a/docs/en/datasets/classify/cifar10.md b/docs/en/datasets/classify/cifar10.md index 513f8383..b4742cbc 100644 --- a/docs/en/datasets/classify/cifar10.md +++ b/docs/en/datasets/classify/cifar10.md @@ -60,7 +60,7 @@ To train a YOLO model on the CIFAR-10 dataset for 100 epochs with an image size ```bash # Start training from a pretrained *.pt model - yolo detect train data=cifar10 model=yolov8n-cls.pt epochs=100 imgsz=32 + yolo classify train data=cifar10 model=yolov8n-cls.pt epochs=100 imgsz=32 ``` ## Sample Images and Annotations @@ -114,7 +114,7 @@ To train a YOLO model on the CIFAR-10 dataset using Ultralytics, you can follow ```bash # Start training from a pretrained *.pt model - yolo detect train data=cifar10 model=yolov8n-cls.pt epochs=100 imgsz=32 + yolo classify train data=cifar10 model=yolov8n-cls.pt epochs=100 imgsz=32 ``` For more details, refer to the model [Training](../../modes/train.md) page. diff --git a/docs/en/datasets/classify/cifar100.md b/docs/en/datasets/classify/cifar100.md index 5110564e..4a8ba4bd 100644 --- a/docs/en/datasets/classify/cifar100.md +++ b/docs/en/datasets/classify/cifar100.md @@ -49,7 +49,7 @@ To train a YOLO model on the CIFAR-100 dataset for 100 epochs with an image size ```bash # Start training from a pretrained *.pt model - yolo detect train data=cifar100 model=yolov8n-cls.pt epochs=100 imgsz=32 + yolo classify train data=cifar100 model=yolov8n-cls.pt epochs=100 imgsz=32 ``` ## Sample Images and Annotations @@ -107,7 +107,7 @@ You can train a YOLO model on the CIFAR-100 dataset using either Python or CLI c ```bash # Start training from a pretrained *.pt model - yolo detect train data=cifar100 model=yolov8n-cls.pt epochs=100 imgsz=32 + yolo classify train data=cifar100 model=yolov8n-cls.pt epochs=100 imgsz=32 ``` For a comprehensive list of available arguments, please refer to the model [Training](../../modes/train.md) page. diff --git a/docs/en/datasets/classify/fashion-mnist.md b/docs/en/datasets/classify/fashion-mnist.md index 21373268..656473ed 100644 --- a/docs/en/datasets/classify/fashion-mnist.md +++ b/docs/en/datasets/classify/fashion-mnist.md @@ -74,7 +74,7 @@ To train a CNN model on the Fashion-MNIST dataset for 100 epochs with an image s ```bash # Start training from a pretrained *.pt model - yolo detect train data=fashion-mnist model=yolov8n-cls.pt epochs=100 imgsz=28 + yolo classify train data=fashion-mnist model=yolov8n-cls.pt epochs=100 imgsz=28 ``` ## Sample Images and Annotations @@ -117,7 +117,7 @@ To train an Ultralytics YOLO model on the Fashion-MNIST dataset, you can use bot === "CLI" ```bash - yolo detect train data=fashion-mnist model=yolov8n-cls.pt epochs=100 imgsz=28 + yolo classify train data=fashion-mnist model=yolov8n-cls.pt epochs=100 imgsz=28 ``` For more detailed training parameters, refer to the [Training page](../../modes/train.md). diff --git a/docs/en/datasets/classify/imagenet.md b/docs/en/datasets/classify/imagenet.md index e5635680..53aabcce 100644 --- a/docs/en/datasets/classify/imagenet.md +++ b/docs/en/datasets/classify/imagenet.md @@ -59,7 +59,7 @@ To train a deep learning model on the ImageNet dataset for 100 epochs with an im ```bash # Start training from a pretrained *.pt model - yolo train data=imagenet model=yolov8n-cls.pt epochs=100 imgsz=224 + yolo classify train data=imagenet model=yolov8n-cls.pt epochs=100 imgsz=224 ``` ## Sample Images and Annotations @@ -120,7 +120,7 @@ To use a pretrained Ultralytics YOLO model for image classification on the Image ```bash # Start training from a pretrained *.pt model - yolo train data=imagenet model=yolov8n-cls.pt epochs=100 imgsz=224 + yolo classify train data=imagenet model=yolov8n-cls.pt epochs=100 imgsz=224 ``` For more in-depth training instruction, refer to our [Training page](../../modes/train.md). diff --git a/docs/en/datasets/classify/imagenet10.md b/docs/en/datasets/classify/imagenet10.md index d7bf55e4..a079986c 100644 --- a/docs/en/datasets/classify/imagenet10.md +++ b/docs/en/datasets/classify/imagenet10.md @@ -45,7 +45,7 @@ To test a deep learning model on the ImageNet10 dataset with an image size of 22 ```bash # Start training from a pretrained *.pt model - yolo train data=imagenet10 model=yolov8n-cls.pt epochs=5 imgsz=224 + yolo classify train data=imagenet10 model=yolov8n-cls.pt epochs=5 imgsz=224 ``` ## Sample Images and Annotations @@ -104,7 +104,7 @@ To test your deep learning model on the ImageNet10 dataset with an image size of ```bash # Start training from a pretrained *.pt model - yolo train data=imagenet10 model=yolov8n-cls.pt epochs=5 imgsz=224 + yolo classify train data=imagenet10 model=yolov8n-cls.pt epochs=5 imgsz=224 ``` Refer to the [Training](../../modes/train.md) page for a comprehensive list of available arguments. diff --git a/docs/en/datasets/classify/imagenette.md b/docs/en/datasets/classify/imagenette.md index b667192a..9a2a128f 100644 --- a/docs/en/datasets/classify/imagenette.md +++ b/docs/en/datasets/classify/imagenette.md @@ -47,7 +47,7 @@ To train a model on the ImageNette dataset for 100 epochs with a standard image ```bash # Start training from a pretrained *.pt model - yolo detect train data=imagenette model=yolov8n-cls.pt epochs=100 imgsz=224 + yolo classify train data=imagenette model=yolov8n-cls.pt epochs=100 imgsz=224 ``` ## Sample Images and Annotations @@ -82,7 +82,7 @@ To use these datasets, simply replace 'imagenette' with 'imagenette160' or 'imag ```bash # Start training from a pretrained *.pt model with ImageNette160 - yolo detect train data=imagenette160 model=yolov8n-cls.pt epochs=100 imgsz=160 + yolo classify train data=imagenette160 model=yolov8n-cls.pt epochs=100 imgsz=160 ``` !!! Example "Train Example with ImageNette320" @@ -103,7 +103,7 @@ To use these datasets, simply replace 'imagenette' with 'imagenette160' or 'imag ```bash # Start training from a pretrained *.pt model with ImageNette320 - yolo detect train data=imagenette320 model=yolov8n-cls.pt epochs=100 imgsz=320 + yolo classify train data=imagenette320 model=yolov8n-cls.pt epochs=100 imgsz=320 ``` These smaller versions of the dataset allow for rapid iterations during the development process while still providing valuable and realistic image classification tasks. @@ -140,7 +140,7 @@ To train a YOLO model on the ImageNette dataset for 100 epochs, you can use the ```bash # Start training from a pretrained *.pt model - yolo detect train data=imagenette model=yolov8n-cls.pt epochs=100 imgsz=224 + yolo classify train data=imagenette model=yolov8n-cls.pt epochs=100 imgsz=224 ``` For more details, see the [Training](../../modes/train.md) documentation page. diff --git a/docs/en/datasets/classify/imagewoof.md b/docs/en/datasets/classify/imagewoof.md index 2a439425..5a76d97f 100644 --- a/docs/en/datasets/classify/imagewoof.md +++ b/docs/en/datasets/classify/imagewoof.md @@ -44,7 +44,7 @@ To train a CNN model on the ImageWoof dataset for 100 epochs with an image size ```bash # Start training from a pretrained *.pt model - yolo detect train data=imagewoof model=yolov8n-cls.pt epochs=100 imgsz=224 + yolo classify train data=imagewoof model=yolov8n-cls.pt epochs=100 imgsz=224 ``` ## Dataset Variants @@ -113,7 +113,7 @@ To train a Convolutional Neural Network (CNN) model on the ImageWoof dataset usi === "CLI" ```bash - yolo detect train data=imagewoof model=yolov8n-cls.pt epochs=100 imgsz=224 + yolo classify train data=imagewoof model=yolov8n-cls.pt epochs=100 imgsz=224 ``` For more details on available training arguments, refer to the [Training](../../modes/train.md) page. diff --git a/docs/en/datasets/classify/mnist.md b/docs/en/datasets/classify/mnist.md index 8f8ad126..ae9be2bc 100644 --- a/docs/en/datasets/classify/mnist.md +++ b/docs/en/datasets/classify/mnist.md @@ -52,7 +52,7 @@ To train a CNN model on the MNIST dataset for 100 epochs with an image size of 3 ```bash # Start training from a pretrained *.pt model - cnn detect train data=mnist model=yolov8n-cls.pt epochs=100 imgsz=28 + yolo classify train data=mnist model=yolov8n-cls.pt epochs=100 imgsz=28 ``` ## Sample Images and Annotations @@ -113,7 +113,7 @@ To train a model on the MNIST dataset using Ultralytics YOLO, you can follow the ```bash # Start training from a pretrained *.pt model - cnn detect train data=mnist model=yolov8n-cls.pt epochs=100 imgsz=28 + yolo classify train data=mnist model=yolov8n-cls.pt epochs=100 imgsz=28 ``` For a detailed list of available training arguments, refer to the [Training](../../modes/train.md) page. diff --git a/docs/en/datasets/obb/index.md b/docs/en/datasets/obb/index.md index b0b548b0..f7708a10 100644 --- a/docs/en/datasets/obb/index.md +++ b/docs/en/datasets/obb/index.md @@ -50,7 +50,7 @@ To train a model using these OBB formats: ```bash # Train a new YOLOv8n-OBB model on the DOTAv2 dataset - yolo detect train data=DOTAv1.yaml model=yolov8n.pt epochs=100 imgsz=640 + yolo obb train data=DOTAv1.yaml model=yolov8n-obb.pt epochs=100 imgsz=640 ``` ## Supported Datasets @@ -125,7 +125,7 @@ Training a YOLOv8 model with OBBs involves ensuring your dataset is in the YOLO ```bash # Train a new YOLOv8n-OBB model on the custom dataset - yolo detect train data=your_dataset.yaml model=yolov8n.pt epochs=100 imgsz=640 + yolo obb train data=your_dataset.yaml model=yolov8n-obb.yaml epochs=100 imgsz=640 ``` This ensures your model leverages the detailed OBB annotations for improved detection accuracy. diff --git a/docs/en/datasets/pose/coco.md b/docs/en/datasets/pose/coco.md index 11cde4dd..52fce86c 100644 --- a/docs/en/datasets/pose/coco.md +++ b/docs/en/datasets/pose/coco.md @@ -71,7 +71,7 @@ To train a YOLOv8n-pose model on the COCO-Pose dataset for 100 epochs with an im ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 + yolo pose train data=coco-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 ``` ## Sample Images and Annotations @@ -133,7 +133,7 @@ Training a YOLOv8 model on the COCO-Pose dataset can be accomplished using eithe ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 + yolo pose train data=coco-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 ``` For more details on the training process and available arguments, check the [training page](../../modes/train.md). diff --git a/docs/en/datasets/pose/coco8-pose.md b/docs/en/datasets/pose/coco8-pose.md index c8d4a375..49295ac4 100644 --- a/docs/en/datasets/pose/coco8-pose.md +++ b/docs/en/datasets/pose/coco8-pose.md @@ -44,7 +44,7 @@ To train a YOLOv8n-pose model on the COCO8-Pose dataset for 100 epochs with an i ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 + yolo pose train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 ``` ## Sample Images and Annotations @@ -105,7 +105,7 @@ To train a YOLOv8n-pose model on the COCO8-Pose dataset for 100 epochs with an i === "CLI" ```bash - yolo detect train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 + yolo pose train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 ``` For a comprehensive list of training arguments, refer to the model [Training](../../modes/train.md) page. diff --git a/docs/en/datasets/pose/index.md b/docs/en/datasets/pose/index.md index 29179d8c..57c20dcb 100644 --- a/docs/en/datasets/pose/index.md +++ b/docs/en/datasets/pose/index.md @@ -82,7 +82,7 @@ The `train` and `val` fields specify the paths to the directories containing the ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 + yolo pose train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640 ``` ## Supported Datasets diff --git a/docs/en/datasets/segment/coco.md b/docs/en/datasets/segment/coco.md index 862ee388..e02b6771 100644 --- a/docs/en/datasets/segment/coco.md +++ b/docs/en/datasets/segment/coco.md @@ -69,7 +69,7 @@ To train a YOLOv8n-seg model on the COCO-Seg dataset for 100 epochs with an imag ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 + yolo segment train data=coco-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 ``` ## Sample Images and Annotations @@ -131,7 +131,7 @@ To train a YOLOv8n-seg model on the COCO-Seg dataset for 100 epochs with an imag ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 + yolo segment train data=coco-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 ``` ### What are the key features of the COCO-Seg dataset? diff --git a/docs/en/datasets/segment/coco8-seg.md b/docs/en/datasets/segment/coco8-seg.md index b781f8be..bcca4a26 100644 --- a/docs/en/datasets/segment/coco8-seg.md +++ b/docs/en/datasets/segment/coco8-seg.md @@ -44,7 +44,7 @@ To train a YOLOv8n-seg model on the COCO8-Seg dataset for 100 epochs with an ima ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 + yolo segment train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 ``` ## Sample Images and Annotations @@ -106,7 +106,7 @@ To train a **YOLOv8n-seg** model on the COCO8-Seg dataset for 100 epochs with an ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 + yolo segment train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 ``` For a thorough explanation of available arguments and configuration options, you can check the [Training](../../modes/train.md) documentation. diff --git a/docs/en/datasets/segment/index.md b/docs/en/datasets/segment/index.md index 27cb4374..f9228c08 100644 --- a/docs/en/datasets/segment/index.md +++ b/docs/en/datasets/segment/index.md @@ -84,7 +84,7 @@ The `train` and `val` fields specify the paths to the directories containing the ```bash # Start training from a pretrained *.pt model - yolo detect train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 + yolo segment train data=coco8-seg.yaml model=yolov8n-seg.pt epochs=100 imgsz=640 ``` ## Supported Datasets