Comments (1)
@useruser2023 hello! Thanks for reaching out and for your efforts in searching for a solution before posting your issue.
The error you're encountering, AttributeError: 'DetectionModel' object has no attribute 'hyp'
, suggests that the model object you're trying to use does not have the hyperparameters (hyp
) attribute that the ComputeLoss
function expects.
The ComputeLoss
function requires the model's hyperparameters to calculate the loss. When you load the model using YOLO("best.pt")
, it does not automatically load the hyperparameters used during training.
To resolve this, you should ensure that the hyperparameters are correctly loaded and associated with your model object. Typically, these hyperparameters are stored in a .yaml
file or within the training script. Make sure to load these hyperparameters and pass them to the ComputeLoss
function or the model object as required.
For further guidance on how to properly set up the loss computation for validation, please refer to the Ultralytics Docs, which provide comprehensive information on using the YOLOv3 repository.
If you continue to face issues, please provide more details about how you're loading the model and where the hyperparameters are defined, and we'll be happy to help you further. Remember, the community and the Ultralytics team are here to support you! ๐
from yolov3.
Related Issues (20)
- About the instructions and code comments HOT 3
- A hopelessly long try to replicate the YOLOv3 kernel HOT 2
- Change in the anchor boxes HOT 10
- โ๏ธClosed per Code of Conduct HOT 1
- no anchor_grid in V9.6.0 yolov3.pt HOT 5
- Convert YOLOv3 dataset format to YOLOv8 HOT 3
- What's the difference between it and Yolov3 by Joseph Redmon ? HOT 7
- Integrating YOLOv8 into YOLOv3 Ultralytics HOT 2
- Seeking Advice on Equivalent YOLOv5 Variant to Standard YOLOv3 HOT 1
- Unexpectedly large trained model size (~200 MB .pt and ~400 MB .onnx) HOT 4
- Training requires much more VRAM than v5/v8 and results in ~200 MB models comparing to <15 MB models of v5/v8 HOT 5
- how to train your yolov8?
- Need info regarding yolov3-tiny anchors, dataset creation and loss function. HOT 5
- yolov3_ros input topic channel problem HOT 5
- Issue with training YOLOv3-tiny from scratch HOT 4
- yolov3.pt HOT 4
- ๅ ณไบ่ฐ็จๆจ็ไปฃ็ ๅ้ๅฐ็ไธไธไบ้ฎ้ข HOT 8
- Bug of incomplete information display HOT 2
- No module named 'ultralytics.yolo' HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
๐ 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. ๐๐๐
-
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 โค๏ธ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from yolov3.