shoplifting detection

[HaldunMatar]

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Question

how I can use yolo to to train and shoplifting scenarios detection - could you give me main steps

Additional

how I can use yolo to to train and shoplifting scenarios detection - could you give me main steps

[UltralyticsAssistant]

👋 Hello @HaldunMatar, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more about using YOLO for your projects:

• Quickstart. Discover how to quickly start training and deploying YOLO models with HUB.
• Datasets: Preparing and Uploading. Learn how to prepare and upload datasets in the YOLO format, crucial for training on specific scenarios like shoplifting.
• Projects: Creating and Managing. Organize your shoplifting detection models into projects for greater efficiency.
• Models: Training and Exporting. Get information on training your models on custom datasets and exporting them for deployment.
• Integrations. Implement your trained models with different integration options for wider applications.
• Inference API. Utilize the Inference API to run predictions in the cloud.

If this is a 🐛 Bug Report, please ensure you provide screenshots and steps to reproduce the issue to assist us in delivering a fix efficiently.

If this is a ❓ Question, it would help if you could share more details, like the specific dataset and model details you intend to use, as well as your environment settings. This information allows us to offer you the most relevant guidance.

Please note this is an automated response, but don't worry, an Ultralytics engineer will be in touch soon to provide additional assistance. Thank you for your patience and interest in using YOLO for shoplifting detection! 🚀

[pderrenger]

@HaldunMatar hello! 😊

Great to hear you're interested in using YOLO for shoplifting detection. Here's a step-by-step guide to help you get started with Ultralytics HUB:

1. Sign Up and Log In: First, create an account on Ultralytics HUB if you haven't already. You can sign up using your Google, Apple, or GitHub accounts, or with your email address.

2. Prepare Your Dataset: Collect and label a dataset that includes images or videos of shoplifting scenarios. Ensure your dataset is well-annotated with bounding boxes around the relevant actions or objects.

3. Upload Your Dataset: Navigate to the Datasets section on Ultralytics HUB and upload your dataset. This will allow you to use it for training your model.

4. Select a Pre-trained Model: Go to the Models section and choose a pre-trained YOLOv5 or YOLOv8 model. These models are trained on the COCO dataset and can be fine-tuned for your specific task.

5. Train Your Model: Use the Ultralytics HUB to start training your model. You can adjust the training parameters, such as the number of epochs, to suit your needs. You can also choose to train using Ultralytics Cloud, Google Colab, or your own agent.

6. Monitor Training: Keep an eye on the training progress through real-time updates on model metrics provided by the HUB.

7. Evaluate and Fine-tune: Once training is complete, evaluate your model's performance. You may need to fine-tune it by adjusting hyperparameters or augmenting your dataset.

8. Deploy Your Model: After achieving satisfactory results, deploy your model for real-time detection using the Ultralytics HUB App on mobile devices or export it to various formats for other platforms.

For more detailed guidance, you can refer to the Ultralytics HUB Docs. If you have any more questions or run into issues, feel free to ask here or join our Discord community for discussions.

Best of luck with your project! 🚀