Maybe you can use the file system object and get files form a specified folder?
async function get_files(total){
const myFolder = 'testfolder';
let files = []
let count =0
fs.readdirSync(myFolder).forEach(file => {
if(count <= total){
file = testFolder + file
files.push(file)
} else {
}
count ++
});
return files
}
Pass the list into the function that loads the images and loop through the array. Also resizing the image to fit your model specifications. I used 100*100 images. This way any image from any folder can be used as training data.
`
async function loadImages(files){
console.log("files",files)
const x_inputs = [];
let l=0
for(let file of files){
const img = await Jimp.read(file).then((img) => {
img.resize(100,100)
return img
})... ... ...
`
Try the number training dataset. I get some very cool results.
I have been fascinated with this for the last week, so I thought I would thank you and provide my feedback.
James.
Maybe you can use the file system object and get files form a specified folder?
async function get_files(total){
}
Pass the list into the function that loads the images and loop through the array. Also resizing the image to fit your model specifications. I used 100*100 images. This way any image from any folder can be used as training data.
`
async function loadImages(files){
console.log("files",files)
const x_inputs = [];
let l=0
for(let file of files){
const img = await Jimp.read(file).then((img) => {
img.resize(100,100)
return img
})... ... ...
`
Try the number training dataset. I get some very cool results.
I have been fascinated with this for the last week, so I thought I would thank you and provide my feedback.
James.