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yolov8n's coco pre-training? #12777

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HuKai97 opened this issue May 17, 2024 · 2 comments
Open
1 task done

yolov8n's coco pre-training? #12777

HuKai97 opened this issue May 17, 2024 · 2 comments
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@HuKai97
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HuKai97 commented May 17, 2024

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Can you send me a copy of the training parameter configuration of yolov8n's coco pre-training?

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@HuKai97 HuKai97 added the question Further information is requested label May 17, 2024
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👋 Hello @HuKai97, thank you for your interest in Ultralytics YOLOv8 🚀! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.

If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it.

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Pip install the ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.

pip install ultralytics

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YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

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@glenn-jocher
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Hello! 👋

For the YOLOv8n model pre-trained on the COCO dataset, you can find the training parameter configuration in the coco.yaml file. Here's a quick example of how you might load and train the model using this configuration:

from ultralytics import YOLO

# Load a pretrained YOLOv8n model
model = YOLO('yolov8n.pt')

# Train the model with COCO dataset configuration
results = model.train(data='coco.yaml', epochs=100, imgsz=640)

This will train the model for 100 epochs with an image size of 640. You can adjust the epochs and imgsz as needed for your specific requirements.

If you need the exact configuration file, it's typically located in the data directory of the repository or can be specified directly in your training script as shown above.

Hope this helps! Let me know if you have any more questions. 😊

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