Comments (1)
Hello!
Sorry for the late reply. I've pushed a commit to
- address this error that the validation and inference code won't support the scan with dimension(s) smaller than the patch size.
- Incorrect padding for data loader in my previous commit will lead to a mismatch in location in the local patch and global scan.
So please try to pull the latest code and rerun the MPL training (as the previous padding was wrong). And the validation (and test/inference) should work for data with dimension(s) smaller than patch size now.
If your data has dimension(s) that is generally smaller than the patch size, you may consider changing the patch size. For instance, if your data is mostly like (200,200,70), you can try patch size at (96,96,48). But this will require retraining from scratch (from MAE pretraining).
Thank you and please let me know if you encounter other questions!
Happy training,
Xuzhe
from mapseg.
Related Issues (4)
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 mapseg.