Object Detection about hub HOT 2 CLOSED

👋 Hello @Permian7, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:

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@Permian7 hello!

Starting an object detection project involves several steps. The initial step is to define the scope and objectives: determine what objects you want to detect and the context in which the detection will take place.

Next, gather and annotate a dataset. This dataset should contain images or videos with instances of the objects of interest, which you'll need to label with bounding boxes to provide ground truth for training a detection model.

Once you have your dataset prepared, you can choose a pre-trained model or framework to fine-tune or train from scratch—considering Ultralytics HUB offers various pre-trained models that could be a good starting point.

After selecting a model, you'll need to configure the training process, including setting hyperparameters, and train the model using your annotated dataset. Following training, evaluate the model's performance using metrics like mAP (mean Average Precision) on a validation set.

Lastly, iterate on this process by tuning your model and improving your dataset based on the performance results until you achieve a satisfactory level of accuracy.

For detailed instructions and best practices on each of these steps, you can refer to the Ultralytics HUB documentation, which will guide you through the process from beginning to end.

Good luck with your object detection project!

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