How confidence score is calculated?

doooooori commented 2 years ago

Search before asking

[X] I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

How can YOLO compute the confidence score at test time? They say they compute it as P (object) *IOU. But, during test time, you don't have the ground truth boxes. How is it possible?

Additional

No response

github-actions[bot] commented 2 years ago

👋 Hello @doooooori, 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.

If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available.

For business inquiries or professional support requests please visit https://ultralytics.com or email support@ultralytics.com.

Requirements

Python>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

git clone https://github.com/ultralytics/yolov5  # clone
cd yolov5
pip install -r requirements.txt  # install

Environments

YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

Google Colab and Kaggle notebooks with free GPU:
Google Cloud Deep Learning VM. See GCP Quickstart Guide
Amazon Deep Learning AMI. See AWS Quickstart Guide
Docker Image. See Docker Quickstart Guide

Status

If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training (train.py), validation (val.py), inference (detect.py) and export (export.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit.

oakkyoakoak commented 2 years ago

Hi, i am same situation like you, i am wondering whether you can figure it out yet.

glenn-jocher commented 11 months ago

@oakkyoakoak hi there! The confidence score in YOLOv5 is calculated as the product of the objectness score (P(object)) and the Intersection over Union (IOU) between the predicted bounding box and the ground truth box. The objectness score represents the probability that the bounding box contains an object. During inference, the model generates bounding boxes and applies the confidence score calculation without requiring ground truth boxes. The confidence score is used to determine the likelihood of the object being present in the bounding box. Let me know if you need further assistance!

ultralytics / yolov5