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Train and predict multiple classes detecting for single object YOLO8 #704
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👋 Hello @SutirthaChakraborty, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:
If this is a 🐛 Bug Report, please provide screenshots and steps to reproduce your problem to help us get started working on a fix. If this is a ❓ Question, please provide as much information as possible, including dataset, model, environment details etc. so that we might provide the most helpful response. We try to respond to all issues as promptly as possible. Thank you for your patience! |
Hello! Thank you for reaching out with your question. To train a model on YOLO8 that can detect multiple classes for a single object, you'll need to adjust your dataset annotations to reflect these hierarchical class relationships. Each image should have annotations for both the specific class (e.g., 'bee') and its broader category (e.g., 'insect'). Here’s a brief guide on how to proceed:
If toggling between two classes still occurs, it might be helpful to look into the confidence thresholds and non-maximum suppression settings to ensure that the model can confidently predict multiple classes for the same object. Let me know if you need further assistance or specific guidance on any of the steps! |
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Question
How can we train a model to detect multiple class of a single object.
For example :
an image of bee, it should be able to detect bee and 'insect'
an image of rat, it should be able to detect 'rat' and 'rodent'
Additional
Right now, it's detecting either of any labels and then toggling between two classes.
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