Closed LiaoChengkk closed 1 month ago
👋 Hello @LiaoChengkk, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.
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We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀!
Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.
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@LiaoChengkk hello!
Thank you for your question and for checking the existing issues and discussions before posting. The smallest object that YOLOv5s can detect in a 640x640 image largely depends on several factors, including the object's size relative to the image, the quality of the training data, and the specific use case.
In general, YOLOv5s can detect objects that occupy at least a few pixels in each dimension. However, for practical purposes, objects that are smaller than 10x10 pixels might be challenging to detect reliably. The model's performance can be improved by ensuring that your training dataset includes a variety of object sizes and that the smaller objects are well-represented.
If you are working with particularly small objects, you might consider:
Feel free to experiment with these suggestions and see what works best for your specific application. If you have any further questions or need more detailed assistance, please let us know!
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Hello! I wonder for a 640*640 image, what is the smallest object that yolov5s can detect?
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