InvoiceNet
coral-ordinal
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| InvoiceNet | coral-ordinal | |
|---|---|---|
| 4 | 2 | |
| 2,389 | 75 | |
| - | - | |
| 3.9 | 0.0 | |
| about 2 months ago | about 2 years ago | |
| Python | Python | |
| MIT License | MIT License |
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InvoiceNet
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How would you annotate resumes for object detection?
You can also possibly look at invoice extraction tools such as https://github.com/naiveHobo/InvoiceNet. They solve a similar issue and are researched fairly well, since there is a big market for that.
- Pdfsandwich
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Extract informations from invoices with machine learning
Also, I would suggest you to use this codebase: https://github.com/naiveHobo/InvoiceNet
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P Information Extraction From A Document
You can check out this repository. It contains an implementation of some recent research in deep learning for information extraction on invoices. https://github.com/naiveHobo/InvoiceNet
coral-ordinal
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[D] Why is Ordinal Regression so overlooked?
The most recent and usable DL attempt I have found is the CORAL/CORN frameworks (keras, pytorch) which have just a few stars, and that's it.
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Hey all, I'm Sebastian Raschka, author of Machine Learning with Pytorch and Scikit-Learn. Please feel free to ask me anything!
Also, I often need to do some custom stuff for my research projects. E.g., take CORAL and CORN as an example (https://raschka-research-group.github.io/coral-pytorch/). Here, I needed custom losses and slight modifications to the forward pass. This was relatively easy to do in PyTorch. Someone was so kind to port it to TensorFlow/Keras (https://github.com/ck37/coral-ordinal/tree/master/coral_ordinal), but the code is much more complicated. For research and tinkering, I much prefer working with PyTorch.
What are some alternatives?
GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
pytorch2keras - PyTorch to Keras model convertor
coral-cnn - Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation
awesome-document-understanding - A curated list of resources for Document Understanding (DU) topic
corn-ordinal-neuralnet - Code and experiments for "Deep Neural Networks for Rank Consistent Ordinal Regression based on Conditional Probabilities"
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
Ordinal_Classifier - Introduce order in your classification within 1 line
ripgrep-all - rga: ripgrep, but also search in PDFs, E-Books, Office documents, zip, tar.gz, etc.
NeuralNetworks - Implementation of a Neural Network that can detect whether a video is in-game or not
OCRmyPDF - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
pycm - Multi-class confusion matrix library in Python