parent
90bc3f6acf
commit
c844aeabe4
@ -14,7 +14,7 @@ tmp_dir = "tmp"
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follow_symlink = false
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follow_symlink = false
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full_bin = ""
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full_bin = ""
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include_dir = []
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include_dir = []
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include_ext = ["go", "tpl", "tmpl", "html"]
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include_ext = ["go", "tpl", "tmpl"] # , "html"
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include_file = []
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include_file = []
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kill_delay = "0s"
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kill_delay = "0s"
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log = "build-errors.log"
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log = "build-errors.log"
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@ -2,7 +2,6 @@ package models
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import (
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import (
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"bytes"
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"bytes"
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"fmt"
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"image"
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"image"
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"image/color"
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"image/color"
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_ "image/jpeg"
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_ "image/jpeg"
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@ -38,8 +37,8 @@ func loadBaseImage(c *Context, id string) {
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case "png":
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case "png":
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case "jpeg":
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case "jpeg":
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default:
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default:
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// TODO better logging
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ModelUpdateStatus(c, id, FAILED_PREPARING)
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fmt.Printf("Found unkown format '%s'\n", format)
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c.Logger.Error("Found unkown format '%s'\n", "format", format)
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panic("Handle diferent files than .png")
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panic("Handle diferent files than .png")
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}
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}
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@ -53,24 +52,26 @@ func loadBaseImage(c *Context, id string) {
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fallthrough
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fallthrough
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case color.GrayModel:
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case color.GrayModel:
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model_color = "greyscale"
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model_color = "greyscale"
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case color.NRGBAModel:
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fallthrough
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case color.YCbCrModel:
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case color.YCbCrModel:
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model_color = "rgb"
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model_color = "rgb"
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default:
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default:
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fmt.Println("Do not know how to handle this color model")
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c.Logger.Error("Do not know how to handle this color model")
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if src.ColorModel() == color.RGBA64Model {
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if src.ColorModel() == color.RGBA64Model {
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fmt.Println("Color is rgb")
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c.Logger.Error("Color is rgb")
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} else if src.ColorModel() == color.NRGBAModel {
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} else if src.ColorModel() == color.NRGBA64Model {
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fmt.Println("Color is nrgb")
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c.Logger.Error("Color is nrgb 64")
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} else if src.ColorModel() == color.AlphaModel {
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} else if src.ColorModel() == color.AlphaModel {
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fmt.Println("Color is alpha")
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c.Logger.Error("Color is alpha")
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} else if src.ColorModel() == color.CMYKModel {
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} else if src.ColorModel() == color.CMYKModel {
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fmt.Println("Color is cmyk")
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c.Logger.Error("Color is cmyk")
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} else {
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} else {
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fmt.Println("Other so assuming color")
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c.Logger.Error("Other so assuming color")
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}
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}
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ModelUpdateStatus(c, id, -1)
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ModelUpdateStatus(c, id, FAILED_PREPARING)
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return
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return
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}
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}
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@ -130,7 +131,7 @@ func handleAdd(handle *Handle) {
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row, err := handle.Db.Query("select id from models where name=$1 and user_id=$2;", name, c.User.Id)
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row, err := handle.Db.Query("select id from models where name=$1 and user_id=$2;", name, c.User.Id)
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if err != nil {
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if err != nil {
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return Error500(err)
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return c.Error500(err)
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}
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}
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if row.Next() {
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if row.Next() {
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@ -143,12 +144,12 @@ func handleAdd(handle *Handle) {
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_, err = handle.Db.Exec("insert into models (user_id, name) values ($1, $2)", c.User.Id, name)
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_, err = handle.Db.Exec("insert into models (user_id, name) values ($1, $2)", c.User.Id, name)
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if err != nil {
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if err != nil {
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return Error500(err)
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return c.Error500(err)
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}
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}
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row, err = handle.Db.Query("select id from models where name=$1 and user_id=$2;", name, c.User.Id)
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row, err = handle.Db.Query("select id from models where name=$1 and user_id=$2;", name, c.User.Id)
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if err != nil {
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if err != nil {
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return Error500(err)
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return c.Error500(err)
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}
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}
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if !row.Next() {
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if !row.Next() {
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@ -158,7 +159,7 @@ func handleAdd(handle *Handle) {
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var id string
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var id string
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err = row.Scan(&id)
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err = row.Scan(&id)
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if err != nil {
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if err != nil {
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return Error500(err)
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return c.Error500(err)
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}
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}
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// TODO mk this path configurable
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// TODO mk this path configurable
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@ -166,17 +167,17 @@ func handleAdd(handle *Handle) {
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err = os.Mkdir(dir_path, os.ModePerm)
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err = os.Mkdir(dir_path, os.ModePerm)
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if err != nil {
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if err != nil {
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return Error500(err)
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return c.Error500(err)
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}
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}
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f, err := os.Create(path.Join(dir_path, "baseimage.png"))
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f, err := os.Create(path.Join(dir_path, "baseimage.png"))
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if err != nil {
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if err != nil {
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return Error500(err)
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return c.Error500(err)
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}
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}
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defer f.Close()
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defer f.Close()
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f.Write(file)
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f.Write(file)
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fmt.Printf("Created model with id %s! Started to proccess image!\n", id)
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c.Logger.Warn("Created model with id %s! Started to proccess image!\n", "id", id)
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go loadBaseImage(c, id)
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go loadBaseImage(c, id)
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Redirect("/models/edit?id="+id, c.Mode, w, r)
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Redirect("/models/edit?id="+id, c.Mode, w, r)
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@ -32,9 +32,12 @@ func testImgForModel(c *Context, model *BaseModel, path string) (result bool) {
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width, height := bounds.Max.X, bounds.Max.Y
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width, height := bounds.Max.X, bounds.Max.Y
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switch src.ColorModel() {
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switch src.ColorModel() {
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case color.Gray16Model: fallthrough
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case color.Gray16Model:
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fallthrough
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case color.GrayModel:
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case color.GrayModel:
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model_color = "greyscale"
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model_color = "greyscale"
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case color.NRGBAModel:
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fallthrough
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case color.YCbCrModel:
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case color.YCbCrModel:
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model_color = "rgb"
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model_color = "rgb"
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default:
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default:
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@ -42,8 +45,8 @@ func testImgForModel(c *Context, model *BaseModel, path string) (result bool) {
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if src.ColorModel() == color.RGBA64Model {
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if src.ColorModel() == color.RGBA64Model {
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c.Logger.Info("Color is rgb")
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c.Logger.Info("Color is rgb")
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} else if src.ColorModel() == color.NRGBAModel {
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} else if src.ColorModel() == color.NRGBA64Model {
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c.Logger.Info("Color is nrgb")
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c.Logger.Info("Color is nrgb 64")
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} else if src.ColorModel() == color.AlphaModel {
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} else if src.ColorModel() == color.AlphaModel {
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c.Logger.Info("Color is alpha")
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c.Logger.Info("Color is alpha")
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} else if src.ColorModel() == color.CMYKModel {
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} else if src.ColorModel() == color.CMYKModel {
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@ -54,7 +57,7 @@ func testImgForModel(c *Context, model *BaseModel, path string) (result bool) {
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return
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return
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}
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}
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if (StringToImageMode(model_color) != model.ImageMode) {
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if StringToImageMode(model_color) != model.ImageMode {
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c.Logger.Warn("Color Mode does not match with model color mode", model_color, model.ImageMode)
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c.Logger.Warn("Color Mode does not match with model color mode", model_color, model.ImageMode)
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return
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return
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}
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}
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@ -10,6 +10,7 @@ import (
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"os"
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"os"
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"os/exec"
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"os/exec"
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"path"
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"path"
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"sort"
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"strconv"
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"strconv"
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"text/template"
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"text/template"
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@ -43,6 +44,7 @@ const (
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MODEL_DEFINITION_STATUS_PRE_INIT ModelDefinitionStatus = 1
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MODEL_DEFINITION_STATUS_PRE_INIT ModelDefinitionStatus = 1
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MODEL_DEFINITION_STATUS_INIT = 2
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MODEL_DEFINITION_STATUS_INIT = 2
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MODEL_DEFINITION_STATUS_TRAINING = 3
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MODEL_DEFINITION_STATUS_TRAINING = 3
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MODEL_DEFINITION_STATUS_PAUSED_TRAINING = 6
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MODEL_DEFINITION_STATUS_TRANIED = 4
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MODEL_DEFINITION_STATUS_TRANIED = 4
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MODEL_DEFINITION_STATUS_READY = 5
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MODEL_DEFINITION_STATUS_READY = 5
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)
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)
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@ -142,6 +144,7 @@ func trainDefinition(c *Context, model *BaseModel, definition_id string, load_pr
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if err != nil {
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if err != nil {
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return
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return
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}
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}
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defer os.RemoveAll(run_path)
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_, err = generateCvs(c, run_path, model.Id)
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_, err = generateCvs(c, run_path, model.Id)
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if err != nil {
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if err != nil {
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@ -174,29 +177,24 @@ func trainDefinition(c *Context, model *BaseModel, definition_id string, load_pr
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"DefId": definition_id,
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"DefId": definition_id,
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"LoadPrev": load_prev,
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"LoadPrev": load_prev,
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"LastModelRunPath": path.Join(getDir(), result_path, "model.keras"),
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"LastModelRunPath": path.Join(getDir(), result_path, "model.keras"),
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"SaveModelPath": path.Join(getDir(), result_path),
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}); err != nil {
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}); err != nil {
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return
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return
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}
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}
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// Run the command
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// Run the command
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out, err := exec.Command("bash", "-c", fmt.Sprintf("cd %s && python run.py", run_path)).Output()
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out, err := exec.Command("bash", "-c", fmt.Sprintf("cd %s && python run.py", run_path)).CombinedOutput()
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if err != nil {
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if err != nil {
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c.Logger.Debug(string(out))
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c.Logger.Debug(string(out))
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return
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return
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}
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}
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c.Logger.Info("Python finished running")
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if err = os.MkdirAll(result_path, os.ModePerm); err != nil {
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if err = os.MkdirAll(result_path, os.ModePerm); err != nil {
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return
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return
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}
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}
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if err = exec.Command("cp", "-r", path.Join(run_path, "model"), path.Join(result_path, "model")).Run(); err != nil {
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return
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}
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if err = exec.Command("cp", "-r", path.Join(run_path, "model.keras"), path.Join(result_path, "model.keras")).Run(); err != nil {
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return
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}
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accuracy_file, err := os.Open(path.Join(run_path, "accuracy.val"))
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accuracy_file, err := os.Open(path.Join(run_path, "accuracy.val"))
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if err != nil {
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if err != nil {
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return
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return
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@ -214,8 +212,6 @@ func trainDefinition(c *Context, model *BaseModel, definition_id string, load_pr
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}
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}
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c.Logger.Info("Model finished training!", "accuracy", accuracy)
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c.Logger.Info("Model finished training!", "accuracy", accuracy)
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os.RemoveAll(run_path)
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return
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return
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}
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}
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@ -236,6 +232,29 @@ func remove[T interface{}](lst []T, i int) []T {
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return append(lst[:i], lst[i+1:]...)
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return append(lst[:i], lst[i+1:]...)
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}
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}
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type TrainModelRow struct {
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id string
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target_accuracy int
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epoch int
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acuracy float64
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}
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type TraingModelRowDefinitions []TrainModelRow
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func (nf TraingModelRowDefinitions) Len() int { return len(nf) }
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func (nf TraingModelRowDefinitions) Swap(i, j int) { nf[i], nf[j] = nf[j], nf[i] }
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func (nf TraingModelRowDefinitions) Less(i, j int) bool {
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return nf[i].acuracy < nf[j].acuracy
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}
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type ToRemoveList []int
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func (nf ToRemoveList) Len() int { return len(nf) }
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func (nf ToRemoveList) Swap(i, j int) { nf[i], nf[j] = nf[j], nf[i] }
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func (nf ToRemoveList) Less(i, j int) bool {
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return nf[i] < nf[j]
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}
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func trainModel(c *Context, model *BaseModel) {
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func trainModel(c *Context, model *BaseModel) {
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definitionsRows, err := c.Db.Query("select id, target_accuracy, epoch from model_definition where status=$1 and model_id=$2", MODEL_DEFINITION_STATUS_INIT, model.Id)
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definitionsRows, err := c.Db.Query("select id, target_accuracy, epoch from model_definition where status=$1 and model_id=$2", MODEL_DEFINITION_STATUS_INIT, model.Id)
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if err != nil {
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if err != nil {
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@ -246,16 +265,11 @@ func trainModel(c *Context, model *BaseModel) {
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}
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}
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defer definitionsRows.Close()
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defer definitionsRows.Close()
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type row struct {
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var definitions TraingModelRowDefinitions = []TrainModelRow{}
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id string
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target_accuracy int
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epoch int
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}
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definitions := []row{}
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for definitionsRows.Next() {
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for definitionsRows.Next() {
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var rowv row
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var rowv TrainModelRow
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rowv.acuracy = 0
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if err = definitionsRows.Scan(&rowv.id, &rowv.target_accuracy, &rowv.epoch); err != nil {
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if err = definitionsRows.Scan(&rowv.id, &rowv.target_accuracy, &rowv.epoch); err != nil {
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c.Logger.Error("Failed to train Model Could not read definition from db!Err:")
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c.Logger.Error("Failed to train Model Could not read definition from db!Err:")
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c.Logger.Error(err)
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c.Logger.Error(err)
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@ -271,23 +285,23 @@ func trainModel(c *Context, model *BaseModel) {
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return
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return
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}
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}
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toTrain := len(definitions)
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firstRound := true
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firstRound := true
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var newDefinitions = []row{}
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finished := false
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copy(newDefinitions, definitions)
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for {
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for {
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var toRemove ToRemoveList = []int{}
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for i, def := range definitions {
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for i, def := range definitions {
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ModelDefinitionUpdateStatus(c, def.id, MODEL_DEFINITION_STATUS_TRAINING)
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ModelDefinitionUpdateStatus(c, def.id, MODEL_DEFINITION_STATUS_TRAINING)
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accuracy, err := trainDefinition(c, model, def.id, !firstRound)
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accuracy, err := trainDefinition(c, model, def.id, !firstRound)
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if err != nil {
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if err != nil {
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c.Logger.Error("Failed to train definition!Err:", "err", err)
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c.Logger.Error("Failed to train definition!Err:", "err", err)
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ModelDefinitionUpdateStatus(c, def.id, MODEL_DEFINITION_STATUS_FAILED_TRAINING)
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ModelDefinitionUpdateStatus(c, def.id, MODEL_DEFINITION_STATUS_FAILED_TRAINING)
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toTrain = toTrain - 1
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toRemove = append(toRemove, i)
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newDefinitions = remove(newDefinitions, i)
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continue
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continue
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}
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}
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def.epoch += EPOCH_PER_RUN
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def.epoch += EPOCH_PER_RUN
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accuracy = accuracy * 100
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accuracy = accuracy * 100
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def.acuracy = accuracy
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if accuracy >= float64(def.target_accuracy) {
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if accuracy >= float64(def.target_accuracy) {
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c.Logger.Info("Found a definition that reaches target_accuracy!")
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c.Logger.Info("Found a definition that reaches target_accuracy!")
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@ -305,30 +319,68 @@ func trainModel(c *Context, model *BaseModel) {
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return
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return
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}
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}
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toTrain = 0
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finished = true
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break
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break
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}
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}
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if def.epoch > MAX_EPOCH {
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if def.epoch > MAX_EPOCH {
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fmt.Printf("Failed to train definition! Accuracy less %f < %d\n", accuracy, def.target_accuracy)
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fmt.Printf("Failed to train definition! Accuracy less %f < %d\n", accuracy, def.target_accuracy)
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ModelDefinitionUpdateStatus(c, def.id, MODEL_DEFINITION_STATUS_FAILED_TRAINING)
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ModelDefinitionUpdateStatus(c, def.id, MODEL_DEFINITION_STATUS_FAILED_TRAINING)
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toTrain = toTrain - 1
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toRemove = append(toRemove, i)
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newDefinitions = remove(newDefinitions, i)
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continue
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continue
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}
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}
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_, err = c.Db.Exec("update model_definition set accuracy=$1, epoch=$2 where id=$3", accuracy, def.epoch, def.id)
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_, err = c.Db.Exec("update model_definition set accuracy=$1, epoch=$2, status=$3 where id=$4", accuracy, def.epoch, MODEL_DEFINITION_STATUS_PAUSED_TRAINING, def.id)
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if err != nil {
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if err != nil {
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c.Logger.Error("Failed to train definition!Err:\n", "err", err)
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c.Logger.Error("Failed to train definition!Err:\n", "err", err)
|
||||||
ModelUpdateStatus(c, model.Id, FAILED_TRAINING)
|
ModelUpdateStatus(c, model.Id, FAILED_TRAINING)
|
||||||
return
|
return
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
copy(definitions, newDefinitions)
|
|
||||||
firstRound = false
|
firstRound = false
|
||||||
if toTrain == 0 {
|
if finished {
|
||||||
break
|
break
|
||||||
}
|
}
|
||||||
|
|
||||||
|
sort.Reverse(toRemove)
|
||||||
|
|
||||||
|
c.Logger.Info("Round done", "toRemove", toRemove)
|
||||||
|
|
||||||
|
for _, n := range toRemove {
|
||||||
|
definitions = remove(definitions, n)
|
||||||
|
}
|
||||||
|
|
||||||
|
len_def := len(definitions)
|
||||||
|
|
||||||
|
if len_def == 0 {
|
||||||
|
break
|
||||||
|
}
|
||||||
|
|
||||||
|
if len_def == 1 {
|
||||||
|
continue
|
||||||
|
}
|
||||||
|
|
||||||
|
sort.Sort(definitions)
|
||||||
|
|
||||||
|
acc := definitions[0].acuracy - 20
|
||||||
|
|
||||||
|
c.Logger.Info("Training models, Highest acc", "acc", acc)
|
||||||
|
|
||||||
|
toRemove = []int{}
|
||||||
|
for i, def := range definitions {
|
||||||
|
if def.acuracy < acc {
|
||||||
|
toRemove = append(toRemove, i)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
c.Logger.Info("Removing due to accuracy", "toRemove", toRemove)
|
||||||
|
|
||||||
|
sort.Reverse(toRemove)
|
||||||
|
for _, n := range toRemove {
|
||||||
|
c.Logger.Warn("Removing definition not fast enough learning", "n", n)
|
||||||
|
definitions = remove(definitions, n)
|
||||||
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
rows, err := c.Db.Query("select id from model_definition where model_id=$1 and status=$2 order by accuracy desc limit 1;", model.Id, MODEL_DEFINITION_STATUS_TRANIED)
|
rows, err := c.Db.Query("select id from model_definition where model_id=$1 and status=$2 order by accuracy desc limit 1;", model.Id, MODEL_DEFINITION_STATUS_TRANIED)
|
||||||
@ -437,14 +489,26 @@ func generateDefinition(c *Context, model *BaseModel, target_accuracy int, numbe
|
|||||||
return failed()
|
return failed()
|
||||||
}
|
}
|
||||||
|
|
||||||
order := 1;
|
order := 1
|
||||||
|
|
||||||
|
// Note the shape of the first layer defines the import size
|
||||||
|
if complexity == 2 {
|
||||||
// Note the shape for now is no used
|
// Note the shape for now is no used
|
||||||
|
width := int(math.Pow(2, math.Floor(math.Log(float64(model.Width))/math.Log(2.0))))
|
||||||
|
height := int(math.Pow(2, math.Floor(math.Log(float64(model.Height))/math.Log(2.0))))
|
||||||
|
c.Logger.Warn("Complexity 2 creating model with smaller size", "width", width, "height", height)
|
||||||
|
err = MakeLayer(c.Db, def_id, order, LAYER_INPUT, fmt.Sprintf("%d,%d,1", width, height))
|
||||||
|
if err != nil {
|
||||||
|
return failed()
|
||||||
|
}
|
||||||
|
order++
|
||||||
|
} else {
|
||||||
err = MakeLayer(c.Db, def_id, order, LAYER_INPUT, fmt.Sprintf("%d,%d,1", model.Width, model.Height))
|
err = MakeLayer(c.Db, def_id, order, LAYER_INPUT, fmt.Sprintf("%d,%d,1", model.Width, model.Height))
|
||||||
if err != nil {
|
if err != nil {
|
||||||
return failed()
|
return failed()
|
||||||
}
|
}
|
||||||
order++;
|
order++
|
||||||
|
}
|
||||||
|
|
||||||
if complexity == 0 {
|
if complexity == 0 {
|
||||||
|
|
||||||
@ -452,12 +516,12 @@ func generateDefinition(c *Context, model *BaseModel, target_accuracy int, numbe
|
|||||||
if err != nil {
|
if err != nil {
|
||||||
return failed()
|
return failed()
|
||||||
}
|
}
|
||||||
order++;
|
order++
|
||||||
|
|
||||||
loop := int(math.Log2(float64(number_of_classes)))
|
loop := int(math.Log2(float64(number_of_classes)))
|
||||||
for i := 0; i < loop; i++ {
|
for i := 0; i < loop; i++ {
|
||||||
err = MakeLayer(c.Db, def_id, order, LAYER_DENSE, fmt.Sprintf("%d,1", number_of_classes*(loop-i)))
|
err = MakeLayer(c.Db, def_id, order, LAYER_DENSE, fmt.Sprintf("%d,1", number_of_classes*(loop-i)))
|
||||||
order++;
|
order++
|
||||||
if err != nil {
|
if err != nil {
|
||||||
ModelUpdateStatus(c, model.Id, FAILED_PREPARING_TRAINING)
|
ModelUpdateStatus(c, model.Id, FAILED_PREPARING_TRAINING)
|
||||||
// TODO improve this response
|
// TODO improve this response
|
||||||
@ -465,17 +529,17 @@ func generateDefinition(c *Context, model *BaseModel, target_accuracy int, numbe
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
} else if (complexity == 1) {
|
} else if complexity == 1 {
|
||||||
|
|
||||||
loop := int((math.Log(float64(model.Width)) / math.Log(float64(10))))
|
loop := int((math.Log(float64(model.Width)) / math.Log(float64(10))))
|
||||||
if loop == 0 {
|
if loop == 0 {
|
||||||
loop = 1;
|
loop = 1
|
||||||
}
|
}
|
||||||
for i := 0; i < loop; i++ {
|
for i := 0; i < loop; i++ {
|
||||||
err = MakeLayer(c.Db, def_id, order, LAYER_SIMPLE_BLOCK, "")
|
err = MakeLayer(c.Db, def_id, order, LAYER_SIMPLE_BLOCK, "")
|
||||||
order++;
|
order++
|
||||||
if err != nil {
|
if err != nil {
|
||||||
return failed();
|
return failed()
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
@ -483,17 +547,49 @@ func generateDefinition(c *Context, model *BaseModel, target_accuracy int, numbe
|
|||||||
if err != nil {
|
if err != nil {
|
||||||
return failed()
|
return failed()
|
||||||
}
|
}
|
||||||
order++;
|
order++
|
||||||
|
|
||||||
loop = int((math.Log(float64(number_of_classes)) / math.Log(float64(10))) / 2)
|
loop = int((math.Log(float64(number_of_classes)) / math.Log(float64(10))) / 2)
|
||||||
if loop == 0 {
|
if loop == 0 {
|
||||||
loop = 1;
|
loop = 1
|
||||||
}
|
}
|
||||||
for i := 0; i < loop; i++ {
|
for i := 0; i < loop; i++ {
|
||||||
err = MakeLayer(c.Db, def_id, order, LAYER_DENSE, fmt.Sprintf("%d,1", number_of_classes*(loop-i)))
|
err = MakeLayer(c.Db, def_id, order, LAYER_DENSE, fmt.Sprintf("%d,1", number_of_classes*(loop-i)))
|
||||||
order++;
|
order++
|
||||||
if err != nil {
|
if err != nil {
|
||||||
return failed();
|
return failed()
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
} else if complexity == 2 {
|
||||||
|
|
||||||
|
loop := int((math.Log(float64(model.Width)) / math.Log(float64(10))))
|
||||||
|
if loop == 0 {
|
||||||
|
loop = 1
|
||||||
|
}
|
||||||
|
for i := 0; i < loop; i++ {
|
||||||
|
err = MakeLayer(c.Db, def_id, order, LAYER_SIMPLE_BLOCK, "")
|
||||||
|
order++
|
||||||
|
if err != nil {
|
||||||
|
return failed()
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
err = MakeLayer(c.Db, def_id, order, LAYER_FLATTEN, "")
|
||||||
|
if err != nil {
|
||||||
|
return failed()
|
||||||
|
}
|
||||||
|
order++
|
||||||
|
|
||||||
|
loop = int((math.Log(float64(number_of_classes)) / math.Log(float64(10))) / 2)
|
||||||
|
if loop == 0 {
|
||||||
|
loop = 1
|
||||||
|
}
|
||||||
|
for i := 0; i < loop; i++ {
|
||||||
|
err = MakeLayer(c.Db, def_id, order, LAYER_DENSE, fmt.Sprintf("%d,1", number_of_classes*(loop-i)))
|
||||||
|
order++
|
||||||
|
if err != nil {
|
||||||
|
return failed()
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
@ -523,20 +619,27 @@ func generateDefinitions(c *Context, model *BaseModel, target_accuracy int, numb
|
|||||||
return c.Error500(err)
|
return c.Error500(err)
|
||||||
}
|
}
|
||||||
|
|
||||||
if (number_of_models == 1) {
|
cls_len := len(cls)
|
||||||
if (model.Width < 100 && model.Height < 100 && len(cls) < 30) {
|
|
||||||
generateDefinition(c, model, target_accuracy, len(cls), 0)
|
if number_of_models == 1 {
|
||||||
|
if model.Width < 100 && model.Height < 100 && cls_len < 30 {
|
||||||
|
generateDefinition(c, model, target_accuracy, cls_len, 0)
|
||||||
|
} else if model.Width > 100 && model.Height > 100 {
|
||||||
|
generateDefinition(c, model, target_accuracy, cls_len, 2)
|
||||||
} else {
|
} else {
|
||||||
generateDefinition(c, model, target_accuracy, len(cls), 1)
|
generateDefinition(c, model, target_accuracy, cls_len, 1)
|
||||||
|
}
|
||||||
|
} else if number_of_models == 3 {
|
||||||
|
for i := 0; i < number_of_models; i++ {
|
||||||
|
generateDefinition(c, model, target_accuracy, cls_len, i)
|
||||||
}
|
}
|
||||||
} else {
|
} else {
|
||||||
// TODO handle incrisea the complexity
|
// TODO handle incrisea the complexity
|
||||||
for i := 0; i < number_of_models; i++ {
|
for i := 0; i < number_of_models; i++ {
|
||||||
generateDefinition(c, model, target_accuracy, len(cls), 0)
|
generateDefinition(c, model, target_accuracy, cls_len, 0)
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
return nil
|
return nil
|
||||||
}
|
}
|
||||||
|
|
||||||
|
2
main.go
2
main.go
@ -4,6 +4,7 @@ import (
|
|||||||
"database/sql"
|
"database/sql"
|
||||||
"fmt"
|
"fmt"
|
||||||
|
|
||||||
|
"github.com/charmbracelet/log"
|
||||||
_ "github.com/lib/pq"
|
_ "github.com/lib/pq"
|
||||||
|
|
||||||
. "git.andr3h3nriqu3s.com/andr3/fyp/logic/models"
|
. "git.andr3h3nriqu3s.com/andr3/fyp/logic/models"
|
||||||
@ -36,6 +37,7 @@ func main() {
|
|||||||
|
|
||||||
_, err = db.Exec("update models set status=$1 where status=$2", models_utils.FAILED_TRAINING, models_utils.TRAINING)
|
_, err = db.Exec("update models set status=$1 where status=$2", models_utils.FAILED_TRAINING, models_utils.TRAINING)
|
||||||
if err != nil {
|
if err != nil {
|
||||||
|
log.Warn("Database might not be on")
|
||||||
panic(err)
|
panic(err)
|
||||||
}
|
}
|
||||||
|
|
||||||
|
@ -14,7 +14,7 @@ create table if not exists models (
|
|||||||
width integer,
|
width integer,
|
||||||
height integer,
|
height integer,
|
||||||
color_mode varchar (20),
|
color_mode varchar (20),
|
||||||
format varchar (20)
|
format varchar (20) default ''
|
||||||
);
|
);
|
||||||
|
|
||||||
-- drop table if exists model_data_point;
|
-- drop table if exists model_data_point;
|
||||||
|
@ -438,27 +438,37 @@
|
|||||||
<thead>
|
<thead>
|
||||||
<tr>
|
<tr>
|
||||||
<th>
|
<th>
|
||||||
Status
|
Training Round Progress
|
||||||
</th>
|
|
||||||
<th>
|
|
||||||
EpochProgress
|
|
||||||
</th>
|
</th>
|
||||||
<th>
|
<th>
|
||||||
Accuracy
|
Accuracy
|
||||||
</th>
|
</th>
|
||||||
|
<th>
|
||||||
|
Status
|
||||||
|
</th>
|
||||||
</tr>
|
</tr>
|
||||||
</thead>
|
</thead>
|
||||||
<tbody>
|
<tbody>
|
||||||
{{ range .Defs}}
|
{{ range .Defs}}
|
||||||
<tr>
|
<tr>
|
||||||
<td>
|
<td>
|
||||||
|
{{.EpochProgress}}/20
|
||||||
|
</td>
|
||||||
|
<td>
|
||||||
|
{{.Accuracy}}%
|
||||||
|
</td>
|
||||||
|
<td style="text-align: center;">
|
||||||
|
{{ if (eq .Status 2) }}
|
||||||
|
<span class="bi bi-book" style="color: green;"></span>
|
||||||
|
{{ else if (eq .Status 3) }}
|
||||||
|
<span class="bi bi-book-half" style="color: green;"></span>
|
||||||
|
{{ else if (eq .Status 6) }}
|
||||||
|
<span class="bi bi-book-half" style="color: orange;"></span>
|
||||||
|
{{ else if (eq .Status -3) }}
|
||||||
|
<span class="bi bi-book-half" style="color: red;"></span>
|
||||||
|
{{ else }}
|
||||||
{{.Status}}
|
{{.Status}}
|
||||||
</td>
|
{{ end }}
|
||||||
<td>
|
|
||||||
{{.EpochProgress}}
|
|
||||||
</td>
|
|
||||||
<td>
|
|
||||||
{{.Accuracy}}
|
|
||||||
</td>
|
</td>
|
||||||
</tr>
|
</tr>
|
||||||
{{ end }}
|
{{ end }}
|
||||||
|
@ -8,7 +8,7 @@ import requests
|
|||||||
|
|
||||||
class NotifyServerCallback(tf.keras.callbacks.Callback):
|
class NotifyServerCallback(tf.keras.callbacks.Callback):
|
||||||
def on_epoch_end(self, epoch, log, *args, **kwargs):
|
def on_epoch_end(self, epoch, log, *args, **kwargs):
|
||||||
requests.get(f'http://localhost:8000/model/epoch/update?model_id={{.Model.Id}}&epoch={epoch}&accuracy={log["accuracy"]}&definition={{.DefId}}')
|
requests.get(f'http://localhost:8000/model/epoch/update?model_id={{.Model.Id}}&epoch={epoch + 1}&accuracy={log["accuracy"]}&definition={{.DefId}}')
|
||||||
|
|
||||||
|
|
||||||
DATA_DIR = "{{ .DataDir }}"
|
DATA_DIR = "{{ .DataDir }}"
|
||||||
@ -160,7 +160,9 @@ model.compile(
|
|||||||
optimizer=tf.keras.optimizers.Adam(),
|
optimizer=tf.keras.optimizers.Adam(),
|
||||||
metrics=['accuracy'])
|
metrics=['accuracy'])
|
||||||
|
|
||||||
his = model.fit(dataset, validation_data= dataset_validation, epochs={{.EPOCH_PER_RUN}}, callbacks=[NotifyServerCallback()], use_multiprocessing = True)
|
his = model.fit(dataset, validation_data= dataset_validation, epochs={{.EPOCH_PER_RUN}}, callbacks=[
|
||||||
|
NotifyServerCallback(),
|
||||||
|
tf.keras.callbacks.EarlyStopping("loss", mode="min", patience=5)], use_multiprocessing = True)
|
||||||
|
|
||||||
acc = his.history["accuracy"]
|
acc = his.history["accuracy"]
|
||||||
|
|
||||||
@ -169,5 +171,5 @@ f.write(str(acc[-1]))
|
|||||||
f.close()
|
f.close()
|
||||||
|
|
||||||
|
|
||||||
tf.saved_model.save(model, "model")
|
tf.saved_model.save(model, "{{ .SaveModelPath }}/model")
|
||||||
model.save("model.keras")
|
model.save("{{ .SaveModelPath }}/model.keras")
|
||||||
|
Loading…
Reference in New Issue
Block a user