Comments (3)
glenn-jocher
commented on June 29, 2024
Hello,
Thank you for bringing this to our attention and for your detailed analysis. You are correct in your understanding. The scenario you described should indeed register the extra detections as false positives. This seems to be an oversight in the current implementation of the process_batch function in the confusion matrix calculation.
We appreciate your input on this matter, as it helps improve the accuracy and functionality of our models. I'll forward this issue to our development team for review and potential inclusion in an upcoming update. If you have any more insights or suggestions, please feel free to share them.
Thanks again for your contribution to making YOLOv8 better!
from ultralytics.
gigumay
commented on June 29, 2024
Thanks! Will you update this thread when/if the bug is fixed?
from ultralytics.
glenn-jocher
commented on June 29, 2024
Hello,
Absolutely! I'll keep you updated right here in this thread as soon as there's any progress on the bug fix. Thank you for your patience and support! 👍
from ultralytics.
Related Issues (20)
- A problem with slow first startup recognition using Gpus HOT 2
- results object attributes and methods missing HOT 4
- mulgpu training error HOT 1
- Error caused by missing data definition in default.yaml. RuntimeError: Trying to create tensor with negative dimension -881: [0, -881] HOT 3
- I have a custom YOLOv8 model for detecting small to medium-sized objects in images. To further enhance inference speed, I aim to prune the model such that it avoids larger object detection layers. This optimization is crucial as my input images consistently fall within small or medium sizes. HOT 7
- Inference Time Variation HOT 4
- YOLOv8-ONNXRuntime doesn't applied to yolo-obb HOT 2
- Very slow data preparation training large dataset HOT 5
- Segmentation mask is too small for large detected objects (1280,500) on image size (1280, 720) HOT 9
- [Classify] The exported model's result differs from pt's result HOT 3
- yolov8n is the latest when using pip install ultralytics? what about v9 and v10?? HOT 2
- Deprecated code, please fix. HOT 1
- How to do cross Validation with yolov8? HOT 1
- How YOLOv8-pose works? HOT 8
- Some questions about fine-tuning and training HOT 3
- Difference between hub and local performance HOT 5
- Add export and inference pipeline for Rockchip / RKNN
- Evaluate Hailo-8 M.2 Module
- Docs Integration Page - Rockchip/RKNN HOT 1
- Docs Integration Page - Hailo AI
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from ultralytics.