image-crop-analysis VS Multi-Type-TD-TSR

Compare image-crop-analysis vs Multi-Type-TD-TSR and see what are their differences.

image-crop-analysis

Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency (by twitter-research)
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image-crop-analysis Multi-Type-TD-TSR
2 4
241 183
3.3% -
0.0 1.4
over 1 year ago 5 months ago
Jupyter Notebook Jupyter Notebook
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

image-crop-analysis

Posts with mentions or reviews of image-crop-analysis. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning image-crop-analysis yet.
Tracking mentions began in Dec 2020.

Multi-Type-TD-TSR

Posts with mentions or reviews of Multi-Type-TD-TSR. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-23.
  • [D] Getting super-level table extraction
    3 projects | reddit.com/r/MachineLearning | 23 Aug 2022
    Recently, I've been researching extracting tables from image documents. First I tried with pdfs, however, the data extraction libraries like camelot are inconsistent. I found a deep learning model called CascadeTabNet. The detection results are okay but cell recognition is poor. I even found Multi-Type-TD-TSR for table extraction. It uses image processing techniques to find the grids. It performs well on structured and bordered tables. However, it messes up if the cell is not properly aligned. Even if extraction is successful, aggregation of multi-line cells, i.e post-processing, is not very obvious.

What are some alternatives?

When comparing image-crop-analysis and Multi-Type-TD-TSR you can also consider the following projects:

vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

Face-Mask-Detection - Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

MetalTranslate - Customizable machine translation in C++

neural-style-transfer - :paintbrush: This repository contains, well-structured Python library and runnable fully prepared Python notebook of the "Neural Style Transfer" algorithm

donut - Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022

Recognition-of-logical-document-structures - First approach for recognizing logical document structures like texts, sentences, segments, words, chars and sentence/segment depth based on recurrent neural network grammars.

oemer - End-to-end Optical Music Recognition (OMR) system. Transcribe phone-taken music sheet image into MusicXML, which can be edited and converted to MIDI.

CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.

100DaysOfML - 100 Days Of Machine Learning. New Content in every 1-2 day and projects every week. The massive 100DaysOfML in building

CascadeTabNet - This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"