320 lines
7.7 KiB
Go
320 lines
7.7 KiB
Go
package backend
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import (
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"bytes"
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"context"
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"encoding/base64"
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"fmt"
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"math"
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"os"
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"path/filepath"
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"time"
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"github.com/disintegration/imaging"
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ort "github.com/yalue/onnxruntime_go"
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"gorm.io/driver/sqlite"
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"gorm.io/gorm"
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)
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var (
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publicImagePath = "./frontend/public/images"
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modelPath = "resnet_epoch_100.onnx"
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// ImageNet 标准化参数
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mean = []float32{0.485, 0.456, 0.406}
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std = []float32{0.229, 0.224, 0.225}
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// 猫品种标签
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labelName = []string{
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"american_shorthair",
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"bengal",
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"british_shorthair",
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"exotic_shorthair",
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"maine_coon",
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"ragdoll",
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"sphynx",
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}
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)
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func NewApp() *App {
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return &App{}
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}
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func (a *App) Startup(ctx context.Context) {
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a.ctx = ctx
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// 设置 ONNX Runtime DLL 路径
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// ort.SetSharedLibraryPath("onnxruntime.dll")
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exeDir, _ := os.Executable()
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println("exeDir", exeDir)
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ort.SetSharedLibraryPath(filepath.Join(filepath.Dir(exeDir), "onnxruntime.dll"))
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// 初始化 ONNX Runtime 环境
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err := ort.InitializeEnvironment()
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if err != nil {
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panic("Failed to initialize ONNX runtime: " + err.Error())
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}
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}
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func preprocessImage(imgData []byte) ([]float32, error) {
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// 解码图片
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reader := bytes.NewReader(imgData)
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img, err := imaging.Decode(reader, imaging.AutoOrientation(true))
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if err != nil {
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return nil, fmt.Errorf("decode image: %w", err)
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}
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// 缩放到 224x224
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img = imaging.Resize(img, 224, 224, imaging.Lanczos)
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// 转换为 float32 数组 (NCHW 格式: 1, 3, 224, 224)
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input := make([]float32, 1*3*224*224)
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bounds := img.Bounds()
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idx := 0
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for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
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for x := bounds.Min.X; x < bounds.Max.X; x++ {
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r, g, b, _ := img.At(x, y).RGBA()
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// RGBA 返回 0-65535，需要转换到 0-255
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rf := float32(r>>8) / 255.0
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gf := float32(g>>8) / 255.0
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bf := float32(b>>8) / 255.0
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// ImageNet 标准化
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input[idx] = (rf - mean[0]) / std[0] // R channel
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input[idx+224*224] = (gf - mean[1]) / std[1] // G channel
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input[idx+224*224*2] = (bf - mean[2]) / std[2] // B channel
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idx++
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}
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}
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return input, nil
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}
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func runInference(input []float32) (string, float64, error) {
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// 创建输入张量 [1, 3, 224, 224]
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inputTensor, err := ort.NewTensor(ort.Shape{1, 3, 224, 224}, input)
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if err != nil {
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return "", 0, fmt.Errorf("create input tensor: %w", err)
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}
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defer inputTensor.Destroy()
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// 创建输出张量 [1, 7]
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outputTensor, err := ort.NewTensor(ort.Shape{1, 7}, make([]float32, 7))
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if err != nil {
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return "", 0, fmt.Errorf("create output tensor: %w", err)
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}
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defer outputTensor.Destroy()
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exeDir, _ := os.Executable()
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println("exeDir222", exeDir)
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// 创建 session 并运行推理
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session, err := ort.NewAdvancedSession(
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filepath.Join(filepath.Dir(exeDir), modelPath),
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[]string{"input"},
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[]string{"output"},
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[]ort.Value{inputTensor},
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[]ort.Value{outputTensor},
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nil,
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)
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if err != nil {
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return "", 0, fmt.Errorf("create session: %w", err)
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}
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defer session.Destroy()
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err = session.Run()
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if err != nil {
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return "", 0, fmt.Errorf("run inference: %w", err)
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}
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// 获取输出
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outputData := outputTensor.GetData()
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// 找最大值的索引
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maxIdx := 0
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maxVal := outputData[0]
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for i := 1; i < len(outputData); i++ {
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if outputData[i] > maxVal {
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maxVal = outputData[i]
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maxIdx = i
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}
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}
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// Softmax 计算置信度
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var sum float64
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for _, v := range outputData {
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sum += math.Exp(float64(v))
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}
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confidence := math.Exp(float64(maxVal)) / sum
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return labelName[maxIdx], confidence, nil
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}
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func (a *App) GormDB() (*gorm.DB, error) {
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db, err := gorm.Open(sqlite.Open("app.db"), &gorm.Config{})
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if err != nil {
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return nil, err
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}
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return db, nil
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}
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func (a *App) UploadImage(data []byte, filename string) Response {
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println("UploadImage")
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uploadsDir := publicImagePath
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err := os.MkdirAll(uploadsDir, 0755)
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if err != nil {
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return Response{Code: 1, Message: "failed", Data: err.Error()}
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}
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ext := filepath.Ext(filename)
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newFilename := fmt.Sprintf("%d%s", time.Now().UnixMilli(), ext)
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filePath := filepath.Join(uploadsDir, newFilename)
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err = os.WriteFile(filePath, data, 0644)
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if err != nil {
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return Response{Code: 1, Message: "failed", Data: err.Error()}
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}
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println("333")
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return Response{Code: 0, Message: "success", Data: newFilename}
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}
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func (a *App) GetImage(filename string) Response {
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filePath := filepath.Join(publicImagePath, filename)
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data, err := os.ReadFile(filePath)
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if err != nil {
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return Response{Code: 1, Message: "failed", Data: err.Error()}
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}
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ext := filepath.Ext(filename)
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mimeType := "image/jpeg"
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if ext == ".png" {
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mimeType = "image/png"
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}
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base64Data := base64.StdEncoding.EncodeToString(data)
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dataURL := "data:image/" + mimeType + ";base64," + base64Data
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return Response{Code: 0, Message: "success", Data: dataURL}
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}
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func (a *App) GetHistory(page int, pageSize int) Response {
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db, err := a.GormDB()
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if err != nil {
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return Response{Code: 1, Message: err.Error()}
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}
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var total int64
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db.Table("history_test").Count(&total)
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var historyList []HistoryWithBreed
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err = db.Table("history_test").Select("history_test.*, breeds_test.brief, breeds_test.name").
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Joins("LEFT JOIN breeds_test ON history_test.breed = breeds_test.id").
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Order("history_test.id DESC").Limit(pageSize).Offset((page - 1) * pageSize).Find(&historyList).Error
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if err != nil {
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return Response{Code: 1, Message: err.Error()}
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}
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historyData := HistoryData{Page: page, PageSize: pageSize, Total: total, List: historyList}
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return Response{Code: 0, Message: "success", Data: historyData}
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}
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func (a *App) Detect(filename string) Response {
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db, err := a.GormDB()
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if err != nil {
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return Response{Code: 1, Message: err.Error()}
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}
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/**
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这里调用模型
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**/
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filePath := filepath.Join(publicImagePath, filename)
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imgData, err := os.ReadFile(filePath)
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if err != nil {
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return Response{Code: 1, Message: "failed to read image: " + err.Error()}
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}
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input, err := preprocessImage(imgData)
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if err != nil {
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return Response{Code: 1, Message: "failed to preprocess: " + err.Error()}
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}
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// 推理
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detectRet, confidence, err := runInference(input)
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if err != nil {
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return Response{Code: 1, Message: "model inference failed: " + err.Error()}
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}
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println("confidence", confidence)
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println("detectRet", detectRet)
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/**
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结束
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**/
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var breed Breed
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err = db.Table("breeds_test").Where("code = ?", detectRet).First(&breed).Error
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if err != nil {
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return Response{Code: 1, Message: err.Error()}
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}
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now := int(time.Now().Unix())
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one := HistoryItem{Img: filename, Breed: int(breed.Id), Date: now}
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result := db.Table("history_test").Create(&one)
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if result.Error != nil {
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return Response{Code: 1, Message: result.Error.Error()}
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}
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detectData := DetectData{
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Id: breed.Id,
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Code: breed.Code,
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Name: breed.Name,
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Brief: breed.Brief,
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ConfidenceLevel: 0.98,
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}
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return Response{Code: 0, Message: "success", Data: detectData}
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}
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func (a *App) DeleteOneHistory(id uint) Response {
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db, err := a.GormDB()
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if err != nil {
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return Response{Code: 1, Message: err.Error()}
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}
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result := db.Table("history_test").Delete(&HistoryItem{}, id)
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if result.Error != nil {
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return Response{Code: 1, Message: result.Error.Error()}
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}
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return Response{Code: 0, Message: "success"}
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}
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func (a *App) ClearHistory() Response {
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db, err := a.GormDB()
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if err != nil {
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return Response{Code: 1, Message: err.Error()}
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}
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result := db.Exec("DELETE FROM history_test")
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if result.Error != nil {
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return Response{Code: 1, Message: result.Error.Error()}
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}
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if err := os.RemoveAll(publicImagePath); err != nil {
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return Response{Code: 1, Message: fmt.Sprintf("failed to remove images: %v", err)}
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}
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if err := os.MkdirAll(publicImagePath, 0755); err != nil {
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return Response{Code: 1, Message: fmt.Sprintf("failed to recreate images dir: %v", err)}
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}
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return Response{Code: 0, Message: "success"}
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}
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