Comments (3)
@AntyRia hi there! 😊
Thank you for your kind words and for using our project!
Regarding your question about incremental training, it's crucial to maintain consistency in class labels between your initial and subsequent training sessions. Specifically:
-
Class Order Consistency: The order of the classes in your
train_classes.txt
should remain the same as in your initial training. This ensures that the model correctly interprets the class indices. -
YAML File Alignment: Ensure that the
train_classes.txt
aligns with the class definitions in your corresponding YAML file. The indices (0, 1, 2, etc.) should consistently map to the same classes (person, head, car, etc.).
Here's a quick example to illustrate:
Initial Training:
train_classes.txt
:person head car
- YAML file:
names: [person, head, car]
Incremental Training:
train_classes.txt
:person head car
- YAML file:
names: [person, head, car]
Maintaining this consistency ensures that the model continues to learn correctly without any misinterpretation of class labels.
If you encounter any issues or have further questions, please feel free to share a minimum reproducible code example. This will help us better understand and address your problem. You can refer to our guide on creating a minimum reproducible example here.
Lastly, please ensure you are using the latest versions of torch
and ultralytics
to avoid any compatibility issues.
Happy training! 🚀
from ultralytics.
Thank you for your reply, this is very important to me!
from ultralytics.
@AntyRia you're welcome! 😊
To ensure we can assist you effectively, could you please provide a minimum reproducible code example? This will help us understand the issue better and work towards a solution. You can find guidance on creating one here.
Additionally, please make sure you're using the latest versions of torch
and ultralytics
. If not, upgrading might resolve the issue.
Looking forward to your response! 🚀
from ultralytics.
Related Issues (20)
- run train HOT 4
- Why when I put Pretrained = False, yolov8 still transfer and freeze weights HOT 4
- YOLOv8 is jointly trained with other models HOT 2
- Optimizer='auto' problem HOT 2
- Docker run yolov8 report error:Killed, OOM HOT 4
- Is there any other way to get faster YOLOv8n results without using GPU HOT 2
- Default training parameters for yolov8n? HOT 6
- Exporting a YOLO model fails when current directory is in a different filesystem HOT 6
- YOLOv8 resizes input images differently when training for classification? HOT 3
- FedAvg with YOLO HOT 6
- YOLOv8, v10, RT-DETR albumentation do not apply HOT 5
- How can i train better my project ? YOLOV8 HOT 14
- Codebase for running YoloV10 with ONNX HOT 8
- xywh returns wrong result while xyxy returns right result HOT 1
- Support distributed evaluation during training process HOT 1
- Is there an example of yolov8n-segn Android split HOT 2
- @glenn-jocher tracker is not working for custom trained models,
- multi input video to YOLOv8 and using bytetrack.yaml return same ID to different object and keep increasing HOT 2
- The engine model RTX3060 exported by RTX4070 cannot be inferred HOT 3
- YOLO(model_yaml).load(model.pt) not work. HOT 5
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.