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digitalmars.D.announce - A program that does OCR(Optical Character Recognition) inspired by

reply Murilo <murilomiranda92 hotmail.com> writes:
Hi everyone. I've spent the last weeks working on a program which 
is able to read and understand text from an image file(OCR) by 
using a rudimentary neural network after training with a large 
amount of images(I made them myself, manually). It even shows a 
map of all the parts of the images that have the highest synaptic 
weights(warmer colors). It was made purely in D using the arsd 
library. Below is the link to it if you wish to take a look. For 
now it only understands upper case letters from the English 
alphabet. I'll be adding more over time. Cheers.
https://github.com/MuriloMir/Optical-Character-Recognition
Dec 05 2019
next sibling parent reply Walter Bright <newshound2 digitalmars.com> writes:
On 12/5/2019 5:07 PM, Murilo wrote:
 Hi everyone. I've spent the last weeks working on a program which is able to 
 read and understand text from an image file(OCR) by using a rudimentary neural 
 network after training with a large amount of images(I made them myself, 
 manually). It even shows a map of all the parts of the images that have the 
 highest synaptic weights(warmer colors). It was made purely in D using the
arsd 
 library. Below is the link to it if you wish to take a look. For now it only 
 understands upper case letters from the English alphabet. I'll be adding more 
 over time. Cheers.
 https://github.com/MuriloMir/Optical-Character-Recognition
Nice work!
Dec 05 2019
parent Murilo <murilomiranda92 hotmail.com> writes:
On Friday, 6 December 2019 at 03:03:54 UTC, Walter Bright wrote:
 Nice work!
Thank you very much, I've updated it now, now it contains also all lowercase letters from 'a' to 'n', but it hasn't trained in order to learn how to read them yet.
Dec 10 2019
prev sibling next sibling parent reply Mathias Lang <pro.mathias.lang gmail.com> writes:
Nice work!

You might want to take a look at the MNIST database (
https://en.wikipedia.org/wiki/MNIST_database) which is freely available and
commonly used to train neural network. It will also allow you to benchmark
your implementation against other algorithms.

On Fri, Dec 6, 2019 at 10:07 AM Murilo via Digitalmars-d-announce <
digitalmars-d-announce puremagic.com> wrote:

 Hi everyone. I've spent the last weeks working on a program which
 is able to read and understand text from an image file(OCR) by
 using a rudimentary neural network after training with a large
 amount of images(I made them myself, manually). It even shows a
 map of all the parts of the images that have the highest synaptic
 weights(warmer colors). It was made purely in D using the arsd
 library. Below is the link to it if you wish to take a look. For
 now it only understands upper case letters from the English
 alphabet. I'll be adding more over time. Cheers.
 https://github.com/MuriloMir/Optical-Character-Recognition
Dec 08 2019
next sibling parent Murilo <murilomiranda92 hotmail.com> writes:
On Monday, 9 December 2019 at 01:58:10 UTC, Mathias Lang wrote:
 Nice work!

 You might want to take a look at the MNIST database ( 
 https://en.wikipedia.org/wiki/MNIST_database) which is freely 
 available and commonly used to train neural network. It will 
 also allow you to benchmark your implementation against other 
 algorithms.
Ahh, thank you very much, I've just saved the link to this database and I've just downloaded it.
Dec 08 2019
prev sibling parent Murilo <murilomiranda92 hotmail.com> writes:
On Monday, 9 December 2019 at 01:58:10 UTC, Mathias Lang wrote:
 Nice work!

 You might want to take a look at the MNIST database ( 
 https://en.wikipedia.org/wiki/MNIST_database) which is freely 
 available and commonly used to train neural network. It will 
 also allow you to benchmark your implementation against other 
 algorithms.
I've taken a look at it and unfortunately it is a file with matrices, not with images, so it does not apply to what I'm doing. But thanks anyway for trying to help me. I guess I'll have to make all of the letters myself. I've already made all uppercase and I've made the lowercase from 'a' to 'n' already.
Dec 10 2019
prev sibling parent reply Andrej Mitrovic <andrej.mitrovich gmail.com> writes:
On Friday, 6 December 2019 at 01:07:38 UTC, Murilo wrote:
 Hi everyone. I've spent the last weeks working on a program 
 which is able to read and understand text from an image 
 file(OCR) by using a rudimentary neural network after training 
 with a large amount of images(I made them myself, manually). It 
 even shows a map of all the parts of the images that have the 
 highest synaptic weights(warmer colors). It was made purely in 
 D using the arsd library. Below is the link to it if you wish 
 to take a look. For now it only understands upper case letters 
 from the English alphabet. I'll be adding more over time. 
 Cheers.
 https://github.com/MuriloMir/Optical-Character-Recognition
Hey! This looks like great work to learn from! Is there any chance you could add a dub file to make it easy to build?
Dec 10 2019
next sibling parent Murilo <murilomiranda92 hotmail.com> writes:
 Hey!

 This looks like great work to learn from! Is there any chance 
 you could add a dub file to make it easy to build?
I don't use DUB. But it is very easy to build, just download it and compile it. There is a file called OCR_all_files.zip which contains everything, download it, unzip it and then just compile normally. It should work. The files that you need to compile are just the files generating.d and source.d.
Dec 10 2019
prev sibling parent Murilo <murilomiranda92 hotmail.com> writes:
 Hey!

 This looks like great work to learn from! Is there any chance 
 you could add a dub file to make it easy to build?
Hey everyone. I've finally finished creating all .png images for all 26 letters in both uppercase and lowercase format. I've uploaded it to the github page already. Keep in mind that the lowercase letters still need to be properly resized and none of them are trained, meaning you can't read lowercase letters yet, but you can already see them or use them for something else. https://github.com/MuriloMir/Optical-Character-Recognition
Dec 19 2019