Comments (1)
CTC tends to produce bimodal confidence distributions in general and can't really be coerced to do differently (although there are a couple of papers that try to do so). Calamari and Kraken use the same implementation from cuDNN so there shouldn't be any/much difference in there apart from whatever interpolation they do in their ensembling. Tesseract's implementation is slightly different because it was written by the same person as the ocropy CTC loss which is slightly smoother than standard CTC (and they incorporate dictionary data into the confidence measure).
Anyway, in general you shouldn't treat the reported confidences of different OCR engines as being in the same metric space. Couldn't you just normalize them to get results closer in line to what you are expecting?
from kraken.
Related Issues (20)
- It there a way to simply call kraken recognizer from code? HOT 1
- finetune error on altos containing > or < as txt HOT 7
- serialization problem when using segmodel that has same name for linetypes and regiontypes.
- bad polygons HOT 28
- Fine-tuned segmentation model fails to determine regions HOT 1
- Segment command with separate baseline and region models? HOT 5
- AttributeError: module 'pkgutil' has no attribute 'ImpImporter'. Did you mean: 'zipimporter'? HOT 1
- Failure to read varying text sizes in a Newspaper page HOT 7
- polygonisation for vertical writing systems HOT 8
- pretrain: UnboundLocalError HOT 1
- Segmentation: batch input not working HOT 1
- Kraken install post-July 20 2024 are all broken because of python-bidi
- No such option: --device , -d (how to switch between gpu and cpu computing?) HOT 2
- fix --no-segmentation bug
- access to kraken.re ! HOT 3
- Invalid bounding polygon computed exception during segmentation HOT 7
- Segmentation requires libcurand and libcufft HOT 1
- Exception when forcing binarization in segtrain command HOT 13
- Exception when using the reduceonplateau parameter in segtrain command
- Is it possible to see what file is being processed in segment command? HOT 2
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 kraken.