Add Hindi हिन्दी and Arabic العربية Docs translations (#6428)
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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@ -8,7 +8,7 @@ keywords: Argoverse dataset, autonomous driving, YOLO, 3D tracking, motion forec
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The [Argoverse](https://www.argoverse.org/) dataset is a collection of data designed to support research in autonomous driving tasks, such as 3D tracking, motion forecasting, and stereo depth estimation. Developed by Argo AI, the dataset provides a wide range of high-quality sensor data, including high-resolution images, LiDAR point clouds, and map data.
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!!! note
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!!! Note
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The Argoverse dataset *.zip file required for training was removed from Amazon S3 after the shutdown of Argo AI by Ford, but we have made it available for manual download on [Google Drive](https://drive.google.com/file/d/1st9qW3BeIwQsnR0t8mRpvbsSWIo16ACi/view?usp=drive_link).
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@ -35,7 +35,7 @@ The Argoverse dataset is widely used for training and evaluating deep learning m
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Argoverse dataset, the `Argoverse.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Argoverse.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Argoverse.yaml).
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!!! example "ultralytics/cfg/datasets/Argoverse.yaml"
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!!! Example "ultralytics/cfg/datasets/Argoverse.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/Argoverse.yaml"
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@ -45,7 +45,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
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To train a YOLOv8n model on the Argoverse dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -80,7 +80,7 @@ The example showcases the variety and complexity of the data in the Argoverse da
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If you use the Argoverse dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -31,7 +31,7 @@ The COCO dataset is widely used for training and evaluating deep learning models
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO dataset, the `coco.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco.yaml).
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!!! example "ultralytics/cfg/datasets/coco.yaml"
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!!! Example "ultralytics/cfg/datasets/coco.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/coco.yaml"
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@ -41,7 +41,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
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To train a YOLOv8n model on the COCO dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -76,7 +76,7 @@ The example showcases the variety and complexity of the images in the COCO datas
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If you use the COCO dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -17,7 +17,7 @@ and [YOLOv8](https://github.com/ultralytics/ultralytics).
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the COCO8 dataset, the `coco8.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/coco8.yaml).
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!!! example "ultralytics/cfg/datasets/coco8.yaml"
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!!! Example "ultralytics/cfg/datasets/coco8.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/coco8.yaml"
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@ -27,7 +27,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
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To train a YOLOv8n model on the COCO8 dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -62,7 +62,7 @@ The example showcases the variety and complexity of the images in the COCO8 data
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If you use the COCO dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -30,7 +30,7 @@ The Global Wheat Head Dataset is widely used for training and evaluating deep le
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Global Wheat Head Dataset, the `GlobalWheat2020.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/GlobalWheat2020.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/GlobalWheat2020.yaml).
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!!! example "ultralytics/cfg/datasets/GlobalWheat2020.yaml"
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!!! Example "ultralytics/cfg/datasets/GlobalWheat2020.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/GlobalWheat2020.yaml"
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@ -40,7 +40,7 @@ A YAML (Yet Another Markup Language) file is used to define the dataset configur
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To train a YOLOv8n model on the Global Wheat Head Dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -75,7 +75,7 @@ The example showcases the variety and complexity of the data in the Global Wheat
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If you use the Global Wheat Head Dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -48,7 +48,7 @@ When using the Ultralytics YOLO format, organize your training and validation im
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Here's how you can use these formats to train your model:
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!!! example ""
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!!! Example ""
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=== "Python"
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@ -93,7 +93,7 @@ If you have your own dataset and would like to use it for training detection mod
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You can easily convert labels from the popular COCO dataset format to the YOLO format using the following code snippet:
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!!! example ""
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!!! Example ""
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=== "Python"
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@ -30,7 +30,7 @@ The Objects365 dataset is widely used for training and evaluating deep learning
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the Objects365 Dataset, the `Objects365.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Objects365.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/Objects365.yaml).
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!!! example "ultralytics/cfg/datasets/Objects365.yaml"
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!!! Example "ultralytics/cfg/datasets/Objects365.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/Objects365.yaml"
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To train a YOLOv8n model on the Objects365 dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -75,7 +75,7 @@ The example showcases the variety and complexity of the data in the Objects365 d
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If you use the Objects365 dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -40,7 +40,7 @@ Open Images V7 is a cornerstone for training and evaluating state-of-the-art mod
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Typically, datasets come with a YAML (Yet Another Markup Language) file that delineates the dataset's configuration. For the case of Open Images V7, a hypothetical `OpenImagesV7.yaml` might exist. For accurate paths and configurations, one should refer to the dataset's official repository or documentation.
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!!! example "OpenImagesV7.yaml"
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!!! Example "OpenImagesV7.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/open-images-v7.yaml"
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@ -50,7 +50,7 @@ Typically, datasets come with a YAML (Yet Another Markup Language) file that del
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To train a YOLOv8n model on the Open Images V7 dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! warning
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!!! Warning
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The complete Open Images V7 dataset comprises 1,743,042 training images and 41,620 validation images, requiring approximately **561 GB of storage space** upon download.
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@ -59,7 +59,7 @@ To train a YOLOv8n model on the Open Images V7 dataset for 100 epochs with an im
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- Verify that your device has enough storage capacity.
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- Ensure a robust and speedy internet connection.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -94,7 +94,7 @@ Researchers can gain invaluable insights into the array of computer vision chall
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For those employing Open Images V7 in their work, it's prudent to cite the relevant papers and acknowledge the creators:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -32,7 +32,7 @@ The SKU-110k dataset is widely used for training and evaluating deep learning mo
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. For the case of the SKU-110K dataset, the `SKU-110K.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/SKU-110K.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/SKU-110K.yaml).
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!!! example "ultralytics/cfg/datasets/SKU-110K.yaml"
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!!! Example "ultralytics/cfg/datasets/SKU-110K.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/SKU-110K.yaml"
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To train a YOLOv8n model on the SKU-110K dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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@ -77,7 +77,7 @@ The example showcases the variety and complexity of the data in the SKU-110k dat
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If you use the SKU-110k dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -28,7 +28,7 @@ The VisDrone dataset is widely used for training and evaluating deep learning mo
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the Visdrone dataset, the `VisDrone.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VisDrone.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VisDrone.yaml).
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!!! example "ultralytics/cfg/datasets/VisDrone.yaml"
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!!! Example "ultralytics/cfg/datasets/VisDrone.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/VisDrone.yaml"
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To train a YOLOv8n model on the VisDrone dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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If you use the VisDrone dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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@ -31,7 +31,7 @@ The VOC dataset is widely used for training and evaluating deep learning models
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the VOC dataset, the `VOC.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VOC.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/VOC.yaml).
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!!! example "ultralytics/cfg/datasets/VOC.yaml"
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!!! Example "ultralytics/cfg/datasets/VOC.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/VOC.yaml"
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To train a YOLOv8n model on the VOC dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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If you use the VOC dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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A YAML (Yet Another Markup Language) file is used to define the dataset configuration. It contains information about the dataset's paths, classes, and other relevant information. In the case of the xView dataset, the `xView.yaml` file is maintained at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/xView.yaml](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/datasets/xView.yaml).
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!!! example "ultralytics/cfg/datasets/xView.yaml"
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!!! Example "ultralytics/cfg/datasets/xView.yaml"
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```yaml
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--8<-- "ultralytics/cfg/datasets/xView.yaml"
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To train a model on the xView dataset for 100 epochs with an image size of 640, you can use the following code snippets. For a comprehensive list of available arguments, refer to the model [Training](../../modes/train.md) page.
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!!! example "Train Example"
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!!! Example "Train Example"
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=== "Python"
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If you use the xView dataset in your research or development work, please cite the following paper:
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!!! note ""
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!!! Note ""
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=== "BibTeX"
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