arnaucube
/
galdric
mirror of https://github.com/arnaucube/galdric.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
7 Commits
1 Branch
0 Tags
31 KiB
 
 
Tree: c3e167726b
Branches Tags
${ item.name }
Create branch ${ searchTerm }
from 'c3e167726b'
${ noResults }
arnaucode c3e167726b adding more filters to images, to get better comparisons in datasets. Current filters: Edge Detection, Grayscale) 7 years ago
.gitignore it works! 7 years ago
LICENSE Initial commit 7 years ago
README.md almost implemented k 7 years ago
color.go it works! 7 years ago
config.json implemented REST server api, to send an image, and return the analyzed content description 7 years ago
errors.go implemented REST server api, to send an image, and return the analyzed content description 7 years ago
imageOperations.go adding more filters to images, to get better comparisons in datasets. Current filters: Edge Detection, Grayscale) 7 years ago
knn.go adding more filters to images, to get better comparisons in datasets. Current filters: Edge Detection, Grayscale) 7 years ago
main.go adding more filters to images, to get better comparisons in datasets. Current filters: Edge Detection, Grayscale) 7 years ago
readConfig.go implemented REST server api, to send an image, and return the analyzed content description 7 years ago
readDataset.go adding more filters to images, to get better comparisons in datasets. Current filters: Edge Detection, Grayscale) 7 years ago
server.go adding more filters to images, to get better comparisons in datasets. Current filters: Edge Detection, Grayscale) 7 years ago
test.sh k neighbours implemented, also adding filters to image to get more comparisons (not finished yet) 7 years ago

README.md

galdric

machine learning server, for image classification

  • Reads all the datasets in the folder /dataset
  • Each image is resized to the same size, configured in the config.json
  • For the input images, calculates the euclidean distances
  • Gets the nearest neighbour
  • Show the result, that is the label of the object in the image

send file over ssh:

scp dataset.tar.gz root@51.255.193.106:/root/galdric

on the server, untar file:

tar -xvzf dataset.tar.gz