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Web software to read handwriting characters of korean, russian and japanese (hiragana) alphabet
License: MIT License
Python 42.01%
JavaScript 54.03%
Dockerfile 3.96%
handwriting's Introduction
Hello there, I'm Javier.
HandWritting : A web app to read handwritten characters in some alphabets.
The available alphabets are hiragana, hangul and cyrillic.
VqePy : Python library that implement a interface to construct spin model representantions and execute variational quantum algorithms.
The available models are Molecules, Fermi-Hubbard and spin models.
The available methods are VQE.
SpinSim.py : Python package that allow to construct matrix representations of spin models and compute some quatities of interest.
SpinSim.jl : Julia version of the SpinSim.py.
SMMCodes : Repository with scripts to simulate different SMM and their differents properties.
C++ quantum circuit : My implementation of a quantum circuit in C++ having a small set of gates.
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handwriting's Issues
It's necessary to update the docker files and docker-compose to adjust the changes done to the folder structure and others.
The character separation to read each character in a picture should be improved, a lot of cases the separation create bad predictions
The error happen when you try to send the draw to the API, the API receive a black image.
Buscar una libreria para realizar testing en la api y en la interfaz
The idea is to restructure all the APIS's code and the model construction to have a more general approach and trying to delete unnecessary code.
The objective is improve the actual front end, here just do the logic and structure of the pages, also improve the actual form used to send the image to the ML API.
Construct a neural network that can predict non-cursive russian characters
Construct a neural network for japanese characters (hiragana) that improve the actual results.
Refactor code deleting bas practices