Comments (2)
Hi @CrazyCrud thanks for the interest in the project! Here are some answers:
- we always filter the border annotations in our extractions results (https://enherit.paris.inria.fr/ or
src/extractor.py
) so that's why they don't show up - I would recommend annotating the x-height representation only (wiki) for example using VIA annotator, and then augmenting the ground-truth to generate borders either directly when converting the via json to images (I will see what I can do for #13 in the upcoming days) or after conversion, with morphological operations
- the labels used to train the default model are
illustration
,text
andtext_border
. There are two options to finetune it: (i) you care about extracting all these elements so you keep the same labels (colors) in your GT and finetuning is straightforward or (ii) you want to finetune on a different list of labels (completely different or a subset, in your casetext
andtext_border
), in that case the final conv1x1 layer would be randomly initialized but you will still strongly benefit from the rest of the pretrained network. The latter (ii) is the one performed to report the finetuned results on the baseline detection benchmarks (cBADs, table 1 and 2 in the paper)
Hope this helps
from docextractor.
@monniert thank you very much for your detailed answer!
I would recommend annotating the x-height representation only (wiki) for example using VIA annotator [...] after conversion, with morphological operations
This sounds like a reasonable approach as you explained how to use erosion to generate colored borders in the other issue.
There are two options to finetune it
So independently of the list of labels, it always seems to be a good idea to use the pretrained model.
I'll now give it a try now and finetune the model. Your answer was very helpful.
from docextractor.
Related Issues (20)
- Trying to train a Text Region detector but failed HOT 6
- Training a Text-Line detector and want to create annotations with x-height+ border automatically HOT 3
- via_converter.py generate with boarders HOT 3
- error HOT 6
- Problem with PolynomialLR HOT 5
- Post-processing step HOT 2
- bug -- tester.py HOT 2
- Demo website down HOT 7
- where is the UI? HOT 1
- [suggestion] Store datasets and models in a data archive HOT 1
- conda conflicts HOT 2
- Parallel Prediction? HOT 1
- [bug] translation.exception.TranslateError: No translation get, you may retry HOT 4
- [bug] KeyError: 'filename' HOT 2
- [suggestion] save detected regions as vgg-json HOT 1
- [suggestion] directly input vgg.json for training from scratch or finetuning HOT 1
- [donate] include FUNDING.yml to accept donations HOT 1
- [suggestion] loading the data on the fly HOT 3
- from line level to word level? HOT 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 docextractor.