How to apply YOLOV8 on a custom dataset prepared by Smart Polygon

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I have prepared a dataset using smart polygon. I want to apply YOLOV8 for object detection. Please help me how can I apply YOLOV8 object detection model on this dataset.

Project Type : Object Detection
OS/Browser : Windows/Google Chrome
Universe Link : Machine Parts Inspection Object Detection Dataset and Pre-Trained Model by Tokushima University

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To apply the YOLOv8 object detection model on your dataset, you can follow these steps:

  1. Create a Roboflow Account: Before you start, you need to create a Roboflow account. Once you do that, you can create a new project in the Roboflow dashboard. Choose the project type as “Object Detection”. source

  2. Upload Your Images: Add data to your newly created project. You can do it via API or through the web interface. If you drag and drop a directory with a dataset in a supported format, the Roboflow dashboard will automatically read the images and annotations together. source

  3. Label Your Images: If you only have images, you can label them in Roboflow Annotate. When starting from scratch, consider annotating large batches of images via API or use the model-assisted labeling tool to speed things up. source

  4. Generate a New Version of Your Dataset: After labeling, you can generate a new version of your dataset. source

  5. Train a YOLOv8 Model: To train a YOLOv8 object detection model on your own data, you can follow the YOLOv8 training guide provided by Roboflow. source

  6. Deploy the Model: Once you’ve uploaded the model weights, your custom trained YOLOv8 model can be built into production applications or shared externally for others to see and use. source

Remember, you can also train a YOLOv8 model using Roboflow, which provides an end-to-end solution with all the tools you need to train a model. YOLOv8 models trained on Roboflow have an infinitely scalable API that you can use to call your model, or can be run on device through Roboflow Inference. source

For more detailed instructions, you can refer to the Roboflow blog and the YouTube tutorial on how to train a YOLOv8 object detection model on a custom dataset using Roboflow.

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