@@ -0,0 +1,6 @@
+datasets
+dataset
+dataset_complet
+*.jpg
+*.jpeg
+*.png

@@ -1,2 +1,10 @@
 # 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

@@ -0,0 +1,57 @@
+package main
+
+import "fmt"
+
+//Color struct, defines the color
+type Color struct{}
+
+var c Color
+
+//DarkGray color
+func (c Color) DarkGray(t string) {
+	fmt.Print("\x1b[30;1m") //dark gray
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}
+
+//Red color
+func (c Color) Red(t string) {
+	fmt.Print("\x1b[31;1m") //red
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}
+
+//Green color
+func (c Color) Green(t string) {
+	fmt.Print("\x1b[32;1m") //green
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}
+
+//Yellow color
+func (c Color) Yellow(t string) {
+	fmt.Print("\x1b[33;1m") //yellow
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}
+
+//Blue color
+func (c Color) Blue(t string) {
+	fmt.Print("\x1b[34;1m") //blue
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}
+
+//Purple color
+func (c Color) Purple(t string) {
+	fmt.Print("\x1b[35;1m") //purple
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}
+
+//Cyan color
+func (c Color) Cyan(t string) {
+	fmt.Print("\x1b[36;1m") //cyan
+	fmt.Println(t)
+	fmt.Print("\x1b[0m") //defaultColor
+}

@@ -0,0 +1,4 @@
+{
+    "imgWidth": 300,
+    "imgHeigh": 300
+}

@@ -0,0 +1,9 @@
+package main
+
+import "fmt"
+
+func check(err error) {
+	if err != nil {
+		fmt.Println(err)
+	}
+}

@@ -0,0 +1,85 @@
+package main
+
+import (
+	"bytes"
+	"image"
+	"image/jpeg"
+	"image/png"
+
+	"github.com/nfnt/resize"
+)
+
+type imgRGBA [][]float64
+
+func dataToImage(data []byte, imageName string) (image.Image, error) {
+	//var histogram imgRGBA
+	reader := bytes.NewReader(data)
+	//var imageExtension = strings.Split(imageName, ".")[1]
+	var img image.Image
+	var err error
+	/*switch imageExtension {
+	case "png":
+		img, err = png.Decode(reader)
+	case "jpg":
+		img, err = jpeg.Decode(reader)
+	case "jpeg":
+		img, err = jpeg.Decode(reader)
+	default:
+		img = nil
+	}
+	*/
+	img, err = jpeg.Decode(reader)
+	if err != nil {
+		return img, err
+	}
+	return img, err
+}
+
+func imageToData(img image.Image, imageName string) ([]byte, error) {
+	buf := new(bytes.Buffer)
+	//var imageExtension = strings.Split(imageName, ".")[1]
+	var err error
+	/*switch imageExtension {
+	case "png":
+		err = png.Encode(buf, img)
+	case "jpg":
+		err = jpeg.Encode(buf, img, nil)
+	case "jpeg":
+		err = jpeg.Encode(buf, img, nil)
+	default:
+		img = nil
+	}*/
+	err = jpeg.Encode(buf, img, nil)
+	if err != nil {
+		return buf.Bytes(), err
+	}
+	return buf.Bytes(), err
+}
+
+func imageToPNG(img image.Image) ([]byte, error) {
+	buf := new(bytes.Buffer)
+	var err error
+	err = png.Encode(buf, img)
+	return buf.Bytes(), err
+}
+
+func imageToHistogram(img image.Image) [][]float64 {
+	bounds := img.Bounds()
+
+	//generate the histogram
+	var histogram [][]float64
+	for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
+		for x := bounds.Min.X; x < bounds.Max.X; x++ {
+			r, g, b, a := img.At(x, y).RGBA()
+			var pixel []float64
+			pixel = append(pixel, float64(r), float64(g), float64(b), float64(a))
+			histogram = append(histogram, pixel)
+		}
+	}
+	return histogram
+}
+
+func Resize(img image.Image) image.Image {
+	r := resize.Resize(uint(config.ImgWidth), uint(config.ImgHeigh), img, resize.Lanczos3)
+	return r
+}

@@ -0,0 +1,30 @@
+package main
+
+func euclideanDist(img1, img2 [][]float64) float64 {
+	var dist float64
+
+	for i := 0; i < len(img1); i++ {
+		for j := 0; j < len(img1[i]); j++ {
+			dist += (img1[i][j] - img2[i][j]) * (img1[i][j] - img2[i][j])
+		}
+	}
+
+	return dist
+}
+
+func knn(dataset Dataset, input [][]float64) string {
+	d := euclideanDist(dataset["Leopards"][0], input)
+	label := "lamp"
+	for k, v := range dataset {
+		//fmt.Println(k)
+		for i := 0; i < len(v); i++ {
+			//fmt.Println(i)
+			dNew := euclideanDist(v[i], input)
+			if dNew < d {
+				d = dNew
+				label = k
+			}
+		}
+	}
+	return label
+}

@@ -0,0 +1,31 @@
+package main
+
+import (
+	"fmt"
+	"strconv"
+	"time"
+)
+
+func main() {
+	readConfig("./config.json")
+
+	c.Cyan("reading images datasets")
+	tStart := time.Now()
+	dataset := readDataset("./dataset")
+	fmt.Print("time spend reading images: ")
+	fmt.Println(time.Since(tStart))
+	fmt.Println("total folders scanned: " + strconv.Itoa(len(dataset)))
+
+	numImages := 0
+	for _, v := range dataset {
+		numImages = numImages + len(v)
+	}
+	c.Cyan("total images in dataset: " + strconv.Itoa(numImages))
+
+	//we have the images in the dataset variable
+	//now, can take images
+	testFile := readImage("./test.jpg")
+	r := knn(dataset, testFile)
+	fmt.Println("seems to be a " + r)
+
+}

@@ -0,0 +1,23 @@
+package main
+
+import (
+	"encoding/json"
+	"fmt"
+	"io/ioutil"
+)
+
+type Config struct {
+	ImgWidth   int      `json:"imgWidth"`
+	ImgHeigh   int      `json:"imgHeigh"`
+}
+
+var config Config
+
+func readConfig(path string) {
+	file, err := ioutil.ReadFile(path)
+	if err != nil {
+		fmt.Println("error: ", err)
+	}
+	content := string(file)
+	json.Unmarshal([]byte(content), &config)
+}

@@ -0,0 +1,74 @@
+package main
+
+import (
+	"fmt"
+	"io/ioutil"
+	"strconv"
+)
+
+//each image is [][]float64, is a array of pixels
+type ImgDataset [][][]float64
+
+type Dataset map[string]ImgDataset
+
+func byteArrayToFloat64Array(b []byte) []float64 {
+	var f []float64
+	for i := 0; i < len(b); i++ {
+		val, _ := strconv.ParseFloat(string(b[i]), 64)
+		/*fmt.Print(string(b[i]) + "-")
+		fmt.Println(val)*/
+		f = append(f, val)
+	}
+	return f
+}
+
+func readImage(path string) [][]float64 {
+	//open image file
+	/*reader, err := os.Open(path)
+	check(err)
+	defer reader.Close()*/
+
+	dat, err := ioutil.ReadFile(path)
+	check(err)
+
+	imageRaw, err := dataToImage(dat, path)
+	check(err)
+
+	//resize the image to standard size
+	image := Resize(imageRaw)
+
+	//convert the image to histogram(RGBA)
+	histogram := imageToHistogram(image)
+	//convert image to bytes
+	/*imgBytes, err := imageToData(image, path)
+	check(err)*/
+
+	//imgFloat := byteArrayToFloat64Array(imgBytes)
+	return histogram
+}
+func readDataset(path string) map[string]ImgDataset {
+	//dataset := make(map[string]ImgDataset)
+	dataset := make(Dataset)
+
+	folders, _ := ioutil.ReadDir(path)
+	for _, folder := range folders {
+		fmt.Println(folder.Name())
+
+		var imgDataset ImgDataset
+
+		folderFiles, _ := ioutil.ReadDir(path + "/" + folder.Name())
+		for _, file := range folderFiles {
+			image := readImage(path + "/" + folder.Name() + "/" + file.Name())
+
+			imgDataset = append(imgDataset, image)
+
+			/*fmt.Println(folder.Name())
+			fmt.Println(file.Name())*/
+		}
+
+		//add the foldername to the Dataset map
+		dataset[folder.Name()] = imgDataset
+	}
+
+	return dataset
+}