Setting up confidence threshold while training

[prasen832]

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Question

How to setup confidence threshold while training yolov5 for segmentation ?

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[github-actions]

👋 Hello @prasen832, 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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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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[glenn-jocher]

@prasen832 hello,

Thank you for your question and for checking the existing issues and discussions! Setting up the confidence threshold is typically done during inference rather than training. However, if you want to adjust the confidence threshold for evaluating your model during training, you can modify the conf parameter in the YOLOv5 configuration.

Here's how you can set the confidence threshold during inference:

import torch

# Load the model
model = torch.hub.load('ultralytics/yolov5', 'yolov5s')

# Set the confidence threshold
model.conf = 0.25  # NMS confidence threshold

# Perform inference
results = model('path/to/your/image.jpg')

For segmentation tasks, you can follow a similar approach. If you are training a segmentation model, you might want to ensure that your evaluation metrics reflect the desired confidence threshold.

If you are encountering issues or have specific requirements during training, please provide a minimum reproducible example so we can better assist you. You can refer to our guide on creating a minimum reproducible example here: Minimum Reproducible Example.

Additionally, make sure you are using the latest versions of torch and the YOLOv5 repository to avoid any outdated issues.

Feel free to reach out if you have any more questions or need further assistance. 😊