I will do yolov8 object detection, defect detection and image segmentation

You need to provide your images or dataset and a clear idea of what should be detected (objects, defects, products, etc.). If your data is not labeled, I can help with annotation in Standard and Premium packages. Around 150–200 images per class is usually enough to start training a good model

Yes. I specialize in training YOLOv8 models on custom datasets. Every model is trained specifically on your data instead of generic pretrained results, so it is tailored for your real use case like defect detection, product identification, or any custom object detection task.

You will get a trained model file (.pt), clean Python inference code, and setup instructions (README). Standard and Premium packages also include a simple demo interface using Streamlit for testing. Premium additionally includes a basic API integration for deployment.

Accuracy depends on dataset quality, labeling, and class complexity. With properly annotated data (200+ images per class), model can achieve strong results typically in the 85–95% range for many real-world detection tasks. I also provide evaluation metrics with every delivery.

Yes. If your dataset is not labeled, I can handle full annotation including bounding boxes and preprocessing. This is included in Standard and Premium packages and ensures your dataset is fully ready for model training without needing any extra tools or services.