🐛 opencv

Dockerfile

@@ -1,6 +1,16 @@
 FROM golang:latest AS backend-builder
 RUN apt update
 RUN apt install -y build-essential
+
+# 安装 OpenCV 开发库和依赖
+RUN apt install -y \
+    libopencv-dev \
+    libopencv-core-dev \
+    libopencv-imgproc-dev \
+    libopencv-imgcodecs-dev \
+    libopencv-videoio-dev \
+    pkg-config
+
 WORKDIR /build
 COPY . .
 ENV CGO_ENABLED=1
@@ -10,7 +20,22 @@ RUN apt install -y upx-ucl
 
 RUN upx --best --lzma bin/server
 
+# 收集所有 OpenCV 运行时需要的 .so 文件
+RUN mkdir -p /opencv-libs && \
+    cp -P /usr/lib/x86_64-linux-gnu/libopencv*.so* /opencv-libs/ 2>/dev/null || true
+
 FROM golang:latest
+
+# 安装 OpenCV 运行时依赖
+RUN apt update && apt install -y \
+    libgl1 \
+    libgomp1 \
+    libglib2.0-0 \
+    && rm -rf /var/lib/apt/lists/*
+
+# 复制 OpenCV .so 文件到运行环境
+COPY --from=backend-builder /opencv-libs/* /usr/lib/x86_64-linux-gnu/
+
 COPY --from=backend-builder /build/bin/server /app/server
 #COPY static /app/static
 #COPY static/*.so /app/

go.mod

@@ -33,6 +33,7 @@ require (
 	github.com/yalue/onnxruntime_go v1.12.1
 	go.uber.org/automaxprocs v1.6.0
 	go.uber.org/zap v1.27.0
+	gocv.io/x/gocv v0.42.0
 	golang.org/x/crypto v0.43.0
 	gorm.io/driver/postgres v1.6.0
 	gorm.io/gorm v1.31.1

go.sum

@@ -244,6 +244,8 @@ go.uber.org/multierr v1.10.0 h1:S0h4aNzvfcFsC3dRF1jLoaov7oRaKqRGC/pUEJ2yvPQ=
 go.uber.org/multierr v1.10.0/go.mod h1:20+QtiLqy0Nd6FdQB9TLXag12DsQkrbs3htMFfDN80Y=
 go.uber.org/zap v1.27.0 h1:aJMhYGrd5QSmlpLMr2MftRKl7t8J8PTZPA732ud/XR8=
 go.uber.org/zap v1.27.0/go.mod h1:GB2qFLM7cTU87MWRP2mPIjqfIDnGu+VIO4V/SdhGo2E=
+gocv.io/x/gocv v0.42.0 h1:AAsrFJH2aIsQHukkCovWqj0MCGZleQpVyf5gNVRXjQI=
+gocv.io/x/gocv v0.42.0/go.mod h1:zYdWMj29WAEznM3Y8NsU3A0TRq/wR/cy75jeUypThqU=
 golang.org/x/arch v0.0.0-20210923205945-b76863e36670 h1:18EFjUmQOcUvxNYSkA6jO9VAiXCnxFY6NyDX0bHDmkU=
 golang.org/x/arch v0.0.0-20210923205945-b76863e36670/go.mod h1:5om86z9Hs0C8fWVUuoMHwpExlXzs5Tkyp9hOrfG7pp8=
 golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=

internal/application/classifier/classifier.go

@@ -1,225 +0,0 @@
-package classifier
-
-import (
-	"bufio"
-	"fmt"
-	_ "image/jpeg"
-	_ "image/png"
-	"likedream-goframe/internal/framework/logger"
-	"os"
-	"path/filepath"
-	"runtime"
-	"strings"
-
-	ort "github.com/yalue/onnxruntime_go"
-	"go.uber.org/zap"
-)
-
-type ImageClassifier struct {
-	session      *ort.AdvancedSession
-	inputShape   []int64
-	classes      []string
-	inputTensor  *ort.Tensor[float32]
-	outputTensor *ort.Tensor[float32]
-}
-
-// NewImageClassifier 创建新的图片分类器
-func NewImageClassifier(modelPath, classesPath string) (*ImageClassifier, error) {
-	// 初始化ONNX Runtime
-	exePath := strings.ToLower(os.Args[0])
-	// 获取绝对路径
-	absPath, err := filepath.Abs(exePath)
-	dir := filepath.Dir(absPath)
-	systemOS := runtime.GOOS
-	switch systemOS {
-	case "windows":
-		dir = filepath.Join(dir, "onnxruntime.dll")
-		break
-	case "darwin":
-		dir = filepath.Join(dir, "onnxruntime.dylib")
-		break
-	case "linux":
-		dir = filepath.Join(dir, "onnxruntime.so")
-		break
-	}
-	ort.SetSharedLibraryPath(dir)
-	err = ort.InitializeEnvironment()
-	if err != nil {
-		logger.Logger.Error("初始化onnx：", zap.String("绝对路径", absPath), zap.String("父文件夹", dir))
-		return nil, fmt.Errorf("初始化ONNX Runtime失败: %v", err)
-	}
-
-	// 加载类别名称
-	classes, err := loadClasses(classesPath)
-	if err != nil {
-		return nil, fmt.Errorf("加载类别失败: %v", err)
-	}
-
-	// 创建session选项
-	options, err := ort.NewSessionOptions()
-	if err != nil {
-		return nil, fmt.Errorf("创建session选项失败: %v", err)
-	}
-	defer options.Destroy()
-
-	// 创建输入输出tensor
-	inputShape := ort.NewShape(1, 3, 224, 224)
-	outputShape := ort.NewShape(1, int64(len(classes)))
-
-	inputTensor, err := ort.NewEmptyTensor[float32](inputShape)
-	if err != nil {
-		return nil, fmt.Errorf("创建输入tensor失败: %v", err)
-	}
-
-	outputTensor, err := ort.NewEmptyTensor[float32](outputShape)
-	if err != nil {
-		inputTensor.Destroy()
-		return nil, fmt.Errorf("创建输出tensor失败: %v", err)
-	}
-
-	// 加载模型
-	session, err := ort.NewAdvancedSession(modelPath,
-		[]string{"input"}, []string{"output"},
-		[]ort.ArbitraryTensor{inputTensor}, []ort.ArbitraryTensor{outputTensor},
-		options)
-	if err != nil {
-		inputTensor.Destroy()
-		outputTensor.Destroy()
-		return nil, fmt.Errorf("加载模型失败: %v", err)
-	}
-
-	return &ImageClassifier{
-		session:      session,
-		inputShape:   []int64{1, 3, 224, 224},
-		classes:      classes,
-		inputTensor:  inputTensor,
-		outputTensor: outputTensor,
-	}, nil
-}
-
-// loadClasses 从文件加载类别名称
-func loadClasses(path string) ([]string, error) {
-	file, err := os.Open(path)
-	if err != nil {
-		return nil, err
-	}
-	defer file.Close()
-
-	var classes []string
-	scanner := bufio.NewScanner(file)
-	for scanner.Scan() {
-		classes = append(classes, scanner.Text())
-	}
-
-	if err := scanner.Err(); err != nil {
-		return nil, err
-	}
-
-	return classes, nil
-}
-
-// Predict 预测图片类别
-func (ic *ImageClassifier) Predict(imgPath string) (string, float32, error) {
-	// 加载并预处理图片
-	inputData, err := ic.preprocessImage(imgPath)
-	if err != nil {
-		return "", 0, fmt.Errorf("预处理图片失败: %v", err)
-	}
-
-	// 设置输入数据
-	copy(ic.inputTensor.GetData(), inputData)
-
-	// 运行推理
-	err = ic.session.Run()
-	if err != nil {
-		return "", 0, fmt.Errorf("推理失败: %v", err)
-	}
-
-	// 获取输出数据
-	outputData := ic.outputTensor.GetData()
-
-	// 找到最大概率的类别
-	maxIdx := 0
-	maxProb := outputData[0]
-	for i, prob := range outputData {
-		if prob > maxProb {
-			maxProb = prob
-			maxIdx = i
-		}
-	}
-
-	// 应用softmax获取概率
-	expSum := float32(0)
-	for _, v := range outputData {
-		expSum += exp(v)
-	}
-	probability := exp(outputData[maxIdx]) / expSum
-
-	return ic.classes[maxIdx], probability, nil
-}
-
-// PredictFromBytes 从字节数据预测图片类别
-func (ic *ImageClassifier) PredictFromBytes(imgData []byte) (string, float32, error) {
-	// 预处理图片
-	inputData, err := ic.preprocessImageBytes(imgData)
-	if err != nil {
-		return "", 0, fmt.Errorf("预处理图片失败: %v", err)
-	}
-
-	// 设置输入数据
-	copy(ic.inputTensor.GetData(), inputData)
-
-	// 运行推理
-	err = ic.session.Run()
-	if err != nil {
-		return "", 0, fmt.Errorf("推理失败: %v", err)
-	}
-
-	// 获取输出数据
-	outputData := ic.outputTensor.GetData()
-
-	// 找到最大概率的类别
-	maxIdx := 0
-	maxProb := outputData[0]
-	for i, prob := range outputData {
-		if prob > maxProb {
-			maxProb = prob
-			maxIdx = i
-		}
-	}
-
-	// 应用softmax获取概率
-	expSum := float32(0)
-	for _, v := range outputData {
-		expSum += exp(v)
-	}
-	probability := exp(outputData[maxIdx]) / expSum
-
-	return ic.classes[maxIdx], probability, nil
-}
-
-// Close 关闭分类器
-func (ic *ImageClassifier) Close() error {
-	if ic.inputTensor != nil {
-		ic.inputTensor.Destroy()
-	}
-	if ic.outputTensor != nil {
-		ic.outputTensor.Destroy()
-	}
-	if ic.session != nil {
-		ic.session.Destroy()
-	}
-	return nil
-}
-
-// exp 计算e的x次方（简单实现）
-func exp(x float32) float32 {
-	// 使用泰勒级数近似
-	result := float32(1.0)
-	term := float32(1.0)
-	for i := 1; i < 20; i++ {
-		term *= x / float32(i)
-		result += term
-	}
-	return result
-}

internal/application/classifier/preprocess.go

@@ -1,120 +0,0 @@
-package classifier
-
-import (
-	"bytes"
-	"image"
-	"os"
-)
-
-// preprocessImage 预处理图片文件
-func (ic *ImageClassifier) preprocessImage(imgPath string) ([]float32, error) {
-	file, err := os.Open(imgPath)
-	if err != nil {
-		return nil, err
-	}
-	defer file.Close()
-
-	img, _, err := image.Decode(file)
-	if err != nil {
-		return nil, err
-	}
-
-	return ic.processImage(img)
-}
-
-// preprocessImageBytes 预处理图片字节数据
-func (ic *ImageClassifier) preprocessImageBytes(imgData []byte) ([]float32, error) {
-	img, _, err := image.Decode(bytes.NewReader(imgData))
-	if err != nil {
-		return nil, err
-	}
-
-	return ic.processImage(img)
-}
-
-// processImage 处理图片为模型输入格式
-func (ic *ImageClassifier) processImage(img image.Image) ([]float32, error) {
-	// 调整图片大小到224x224
-	resized := resizeImage(img, 224, 224)
-
-	// 转换为float32数组，并进行归一化
-	// ImageNet的均值和标准差
-	mean := []float32{0.485, 0.456, 0.406}
-	std := []float32{0.229, 0.224, 0.225}
-
-	data := make([]float32, 3*224*224)
-
-	for y := 0; y < 224; y++ {
-		for x := 0; x < 224; x++ {
-			r, g, b, _ := resized.At(x, y).RGBA()
-
-			// 转换为0-1范围
-			rNorm := float32(r) / 65535.0
-			gNorm := float32(g) / 65535.0
-			bNorm := float32(b) / 65535.0
-
-			// 应用归一化
-			idx := y*224 + x
-			data[idx] = (rNorm - mean[0]) / std[0]           // R通道
-			data[224*224+idx] = (gNorm - mean[1]) / std[1]   // G通道
-			data[2*224*224+idx] = (bNorm - mean[2]) / std[2] // B通道
-		}
-	}
-
-	return data, nil
-}
-
-// resizeImage 调整图片大小
-func resizeImage(img image.Image, width, height int) image.Image {
-	bounds := img.Bounds()
-	srcW := bounds.Dx()
-	srcH := bounds.Dy()
-
-	dst := image.NewRGBA(image.Rect(0, 0, width, height))
-
-	for y := 0; y < height; y++ {
-		for x := 0; x < width; x++ {
-			// 简单的最近邻插值
-			srcX := x * srcW / width
-			srcY := y * srcH / height
-
-			if srcX >= srcW {
-				srcX = srcW - 1
-			}
-			if srcY >= srcH {
-				srcY = srcH - 1
-			}
-
-			dst.Set(x, y, img.At(srcX, srcY))
-		}
-	}
-
-	return dst
-}
-
-// centerCrop 中心裁剪图片
-func centerCrop(img image.Image, size int) image.Image {
-	bounds := img.Bounds()
-	width := bounds.Dx()
-	height := bounds.Dy()
-
-	var x0, y0 int
-	if width > height {
-		x0 = (width - height) / 2
-		y0 = 0
-		width = height
-	} else {
-		x0 = 0
-		y0 = (height - width) / 2
-		height = width
-	}
-
-	cropped := image.NewRGBA(image.Rect(0, 0, width, height))
-	for y := 0; y < height; y++ {
-		for x := 0; x < width; x++ {
-			cropped.Set(x, y, img.At(x0+x, y0+y))
-		}
-	}
-
-	return resizeImage(cropped, size, size)
-}

internal/application/classifier/resolver.go

@@ -1,17 +0,0 @@
-package classifier
-
-import "likedream-goframe/internal/utils"
-
-var imageClassifier, _ = NewImageClassifier("static/model.onnx", "static/classes.txt")
-
-// 图片数据 & 类别名称
-// return 是否匹配
-func ClassifyImage(imgData []byte, className string) bool {
-	if imageClassifier == nil {
-		c, err := NewImageClassifier("static/model.onnx", "static/classes.txt")
-		utils.OkOrPanic(err)
-		imageClassifier = c
-	}
-	name, _, _ := imageClassifier.PredictFromBytes(imgData)
-	return className == name
-}

internal/application/cpdaily/login/cas.go

@@ -16,10 +16,12 @@ import (
 	"net/http"
 	"net/url"
 	"regexp"
+	"slices"
 	"strings"
 	"time"
 
 	"github.com/PuerkitoBio/goquery"
+	"github.com/avast/retry-go/v4"
 	"github.com/deatil/go-cryptobin/cryptobin/crypto"
 	"github.com/samber/oops"
 	"github.com/tidwall/gjson"
@@ -188,20 +190,35 @@ func (c *CpdailyCasLogin) Login(ctx context.Context, schoolDetail *school.School
 	} else {
 		allInputs["password"] = encryptCasPassword(password, salt)
 	}
-
+	var SliderCaptchaIds = []string{"1018764144934965"}
 	// 判断是否需要验证码
 	if isCasNeedCaptcha(ctx, loginResponseUrl, loginType, username, c.client) {
-		// 解决验证码
-		captchaUrl := getCasCaptchaUrl(loginResponseUrl, loginType)
+		// 如果是滑块验证码
+		if slices.Contains(SliderCaptchaIds, schoolDetail.Id) {
+			e := retry.Do(func() error {
+				return utils.Catch(func() {
+					captchaUrl := getCasSliderCaptchaUrl(loginResponseUrl)
+					verifyUrl := getCasSliderVerifyUrl(loginResponseUrl)
+					ResolveCasSliderCaptcha(ctx, captchaUrl, verifyUrl, c.client)
+				})
+			}, retry.MaxDelay(15*time.Second), retry.Attempts(5), retry.Context(ctx))
+			if e != nil {
+				utils.OkOrPanic(errors.NewBusinessError(503, "滑块验证码解析失败").WithInnerError(e), oops.WithContext(ctx).Wrap)
+			}
+		} else {
+			// 解决常规图片验证码
+			captchaUrl := getCasCaptchaUrl(loginResponseUrl, loginType)
 
-		captchaResult := ResolveOcrCaptcha(ctx, captchaUrl, c.client)
+			captchaResult := ResolveOcrCaptcha(ctx, captchaUrl, c.client)
 
-		switch loginType {
-		case 0:
-			allInputs["captchaResponse"] = captchaResult
-		default:
-			allInputs["captcha"] = captchaResult
+			switch loginType {
+			case 0:
+				allInputs["captchaResponse"] = captchaResult
+			default:
+				allInputs["captcha"] = captchaResult
+			}
 		}
+
 	}
 
 	loginPostResponse, err := c.client.R().
@@ -529,3 +546,12 @@ func getCasCaptchaUrl(url *url.URL, loginType int) string {
 		return fmt.Sprintf("%s://%s/authserver/getCaptcha.htl", url.Scheme, url.Host)
 	}
 }
+
+func getCasSliderCaptchaUrl(url *url.URL) string {
+	// /authserver/common/openSliderCaptcha.htl?_=1762873725346
+	return fmt.Sprintf("%s://%s/authserver/common/openSliderCaptcha.htl", url.Scheme, url.Host)
+}
+
+func getCasSliderVerifyUrl(url *url.URL) string {
+	return fmt.Sprintf("%s://%s/authserver/common/verifySliderCaptcha.htl", url.Scheme, url.Host)
+}

internal/application/cpdaily/login/ocr.go

@@ -2,71 +2,53 @@ package login
 
 import (
 	"context"
+	"fmt"
 	"io"
-	"likedream-goframe/internal/application/httpclient"
-	"likedream-goframe/internal/common/cst"
+	"likedream-goframe/internal/application/recognizer/ddddocr"
+	"likedream-goframe/internal/framework/logger"
 	"likedream-goframe/internal/utils"
+	"os"
 
-	"github.com/gogf/gf/v2/frame/g"
 	"github.com/samber/oops"
-	"github.com/tidwall/gjson"
+	"go.uber.org/zap"
 	"resty.dev/v3"
 )
 
 func ResolveOcrCaptcha(ctx context.Context, url string, client *resty.Client) string {
-	captchaResponse, err := client.R().
-		WithContext(ctx).
-		Get(url)
-
-	utils.OkOrPanic(err, func(err error) error {
-		return oops.
-			With("captchaUrl", url).
-			WithContext(ctx).
-			Wrap(err)
-	})
-
-	defer func() {
-		_ = captchaResponse.Body.Close()
-	}()
-
-	ocrUrl := g.Cfg().MustGetWithEnv(ctx, cst.ConfigOcrServerUrl).String()
-
-	ocrResponse, err := httpclient.Common.R().
-		SetMultipartFields(&resty.MultipartField{
-			Name:        "file",
-			FileName:    "captcha.jpg",
-			ContentType: captchaResponse.Header().Get("Content-Type"),
-			Reader:      captchaResponse.Body,
-		}).
-		WithContext(ctx).
-		Post(ocrUrl + "/ocr")
-
-	utils.OkOrPanic(err, func(err error) error {
-		return oops.
-			With("captchaUrl", url).
-			WithContext(ctx).
-			Wrap(err)
-	})
-
-	defer func() {
-		_ = ocrResponse.Body.Close()
-	}()
-
-	responseBytes, err := io.ReadAll(ocrResponse.Body)
-	utils.OkOrPanic(err)
-
-	responseJSON := gjson.ParseBytes(responseBytes)
-
-	data := responseJSON.Get("data").String()
-
-	if data == "" {
-		utils.OkOrPanic(oops.
-			In("ResolveOcrCaptcha").
-			With("captchaUrl", url).
-			With("message", responseJSON.Get("message").String()).
-			WithContext(ctx).
-			New("OCR服务返回数据为空"))
-	}
-
+	codePath := DownCode2File(ctx, url, client)
+	img, _ := utils.ReadImg(codePath) //读取验证码图片
+	data := ddddocr.AutoOCRVerification(img)
 	return data
 }
+
+func DownCode2File(ctx context.Context, url string, client *resty.Client) string {
+	res, err := client.R().
+		WithContext(ctx).
+		Get(url)
+	utils.OkOrPanic(err, func(err error) error {
+		return oops.
+			With("captchaUrl", url).
+			WithContext(ctx).
+			Wrap(err)
+	})
+	defer res.Body.Close()
+
+	codeFileName := "code" + utils.GenerateRandomString(16) //生成验证码文件名称
+	codeFileName += ".png"
+	utils.PathExistForCreate("./assets/code/") //检测是否存在路径，如果不存在则创建
+	filepath := fmt.Sprintf("./assets/code/%s", codeFileName)
+	file, err := os.Create(filepath)
+	if err != nil {
+		logger.Logger.Error("生成验证码失败", zap.Error(err))
+		return ""
+	}
+
+	_, err = io.Copy(file, res.Body)
+	if err != nil {
+		logger.Logger.Error("生成验证码失败", zap.Error(err))
+		return ""
+	}
+
+	file.Close()
+	return filepath
+}

internal/application/cpdaily/login/slider.go

@@ -0,0 +1,67 @@
+package login
+
+import (
+	"context"
+	"fmt"
+	"io"
+	"likedream-goframe/internal/application/recognizer/slider"
+	"likedream-goframe/internal/common/errors"
+	"likedream-goframe/internal/utils"
+
+	"github.com/bytedance/sonic"
+	"github.com/samber/oops"
+	"resty.dev/v3"
+)
+
+type CasSliderCaptchaReponse struct {
+	BigImage   string `json:"bigImage"`
+	SmallImage string `json:"smallImage"`
+	TagWidth   int    `json:"tagWidth"`
+	YHeight    int    `json:"yHeight"`
+}
+
+type CasSliderResult struct {
+	ErrorCode int    `json:"errorCode"`
+	ErrorMsg  string `json:"errorMsg"`
+}
+
+func ResolveCasSliderCaptcha(ctx context.Context, captchaUrl string, verifyUrl string, client *resty.Client) {
+	res, err := client.R().
+		WithContext(ctx).
+		Get(captchaUrl)
+	utils.OkOrPanic(err, func(err error) error {
+		return oops.
+			With("captchaUrl", captchaUrl).
+			WithContext(ctx).
+			Wrap(err)
+	})
+	defer res.Body.Close()
+	bytes, _ := io.ReadAll(res.Body)
+	var captcha CasSliderCaptchaReponse
+	sonic.Unmarshal(bytes, &captcha)
+	width := slider.VerifySliderWidthByBase64(captcha.BigImage, captcha.SmallImage)
+	res2, err2 := client.R().
+		WithContext(ctx).
+		SetFormData(map[string]string{
+			"canvasLength": "280",
+			"moveLength":   fmt.Sprintf("%d", width),
+		}).
+		Post(verifyUrl)
+	utils.OkOrPanic(err2, func(err error) error {
+		return oops.
+			With("verifyUrl", verifyUrl).
+			WithContext(ctx).
+			Wrap(err)
+	})
+	defer res2.Body.Close()
+	bytes, _ = io.ReadAll(res2.Body)
+	str := string(bytes)
+	if len(str) > 0 {
+		var result CasSliderResult
+		sonic.Unmarshal(bytes, &result)
+		if result.ErrorCode != 1 {
+			utils.OkOrPanic(oops.WithContext(ctx).Wrap(errors.NewBusinessError(500, "滑块解析错误")))
+		}
+	}
+
+}

internal/application/cpdaily/task/sign.go

@@ -384,18 +384,14 @@ func (c *CpdailyAutoSignTask) ParseFormJson(ctx context.Context, rawJson map[str
 	}
 	list = append(list, dto)
 
-	var current uint = 1
-
 	if isPhoto := rows["isPhoto"]; isPhoto != nil && isPhoto.Int() == 1 {
 		dto = &formtype.CpTaskFormItem{
 			Title:    "签到照片",
 			ColName:  "signImg",
 			Type:     formtype.ItemTypeImage,
 			Required: true,
-			Number:   current,
 		}
 		list = append(list, dto)
-		current++
 	}
 
 	// 是否范围外签到
@@ -404,7 +400,6 @@ func (c *CpdailyAutoSignTask) ParseFormJson(ctx context.Context, rawJson map[str
 		ColName:  "isMalposition",
 		Type:     formtype.ItemTypeSingle,
 		Required: true,
-		Number:   current,
 		Options: []formtype.CpTaskFormItemOption{
 			{
 				Content:      "是",
@@ -418,7 +413,6 @@ func (c *CpdailyAutoSignTask) ParseFormJson(ctx context.Context, rawJson map[str
 		},
 	}
 	list = append(list, dto)
-	current++
 
 	// 范围外签到原因
 	dto = &formtype.CpTaskFormItem{
@@ -427,16 +421,15 @@ func (c *CpdailyAutoSignTask) ParseFormJson(ctx context.Context, rawJson map[str
 		Type:     formtype.ItemTypeInput,
 		Required: true,
 		LogicWid: "abnormalReason",
-		Number:   current,
 	}
 	list = append(list, dto)
-	current++
 
+	current := uint(1)
 	// 处理额外字段
 	if isNeedExtra := rows["isNeedExtra"]; isNeedExtra != nil && isNeedExtra.Int() == 1 {
 		extraField := rows["extraField"].Array()
-		for i, field := range extraField {
-			fieldObj := field.(map[string]*gvar.Var)
+		for _, field := range extraField {
+			fieldObj := gvar.New(field).MapStrVar()
 			title := fieldObj["title"].String()
 			isRequired := fieldObj["isRequired"].Bool()
 			hasOtherItems := fieldObj["hasOtherItems"].Bool()
@@ -445,16 +438,17 @@ func (c *CpdailyAutoSignTask) ParseFormJson(ctx context.Context, rawJson map[str
 				Title:    title,
 				ColName:  title,
 				Type:     formtype.ItemTypeSingle,
-				Number:   uint(i),
+				Number:   current,
 				Required: isRequired,
 				IsOther:  hasOtherItems,
 			}
+			current++
 
 			// 处理选项
 			extraFieldItems := fieldObj["extraFieldItems"].Array()
 			var options []formtype.CpTaskFormItemOption
 			for _, item := range extraFieldItems {
-				itemObj := item.(map[string]*gvar.Var)
+				itemObj := gvar.New(item).MapStrVar()
 				option := formtype.CpTaskFormItemOption{
 					Content:      itemObj["content"].String(),
 					IsOtherItems: itemObj["isOtherItems"].Bool(),
@@ -554,7 +548,9 @@ func (c *CpdailyAutoSignTask) FillCustomForm(ctx context.Context, form map[strin
 				ticket = submitCaptchaResolver.GetCaptchaTicket(ctx, captchaInfo)
 			})
 		}, retry.MaxDelay(15*time.Second), retry.Attempts(5), retry.Context(ctx))
-		utils.OkOrPanic(errors.NewBusinessError(503, "提交验证码识别失败").WithInnerError(e), oops.WithContext(ctx).Wrap)
+		if e != nil {
+			utils.OkOrPanic(errors.NewBusinessError(503, "提交验证码识别失败").WithInnerError(e), oops.WithContext(ctx).Wrap)
+		}
 
 		resultForm["ticket"] = gvar.New(ticket)
 	} else {
@@ -577,8 +573,9 @@ func (c *CpdailyAutoSignTask) FillCustomForm(ctx context.Context, form map[strin
 		var extraFieldItemValues []map[string]*gvar.Var
 
 		for i, field := range extraField {
+			current := uint(i + 1)
 			// 检查数字是否在范围内
-			found := slices.Contains(numbers, uint(i))
+			found := slices.Contains(numbers, current)
 			if !found {
 				utils.OkOrPanic(errors.NewBusinessError(500, "非法的额外信息数据"), oops.WithContext(ctx).Wrap)
 			}
@@ -586,7 +583,7 @@ func (c *CpdailyAutoSignTask) FillCustomForm(ctx context.Context, form map[strin
 			// 找到对应的参数
 			var targetParam *formtype.CpTaskFormItem
 			for _, v := range paramList {
-				if v.Number == uint(i) {
+				if v.Number == current {
 					targetParam = v
 					break
 				}
@@ -596,7 +593,7 @@ func (c *CpdailyAutoSignTask) FillCustomForm(ctx context.Context, form map[strin
 				continue
 			}
 
-			fieldObj := field.(map[string]*gvar.Var)
+			fieldObj := gvar.New(field).MapStrVar()
 			fieldTitle := fieldObj["title"].String()
 
 			if targetParam.Title != fieldTitle {
@@ -607,7 +604,7 @@ func (c *CpdailyAutoSignTask) FillCustomForm(ctx context.Context, form map[strin
 			var extraFieldItemValue map[string]*gvar.Var
 
 			for _, item := range extraFieldItems {
-				itemObj := item.(map[string]*gvar.Var)
+				itemObj := gvar.New(item).MapStrVar()
 				content := itemObj["content"].String()
 
 				if content == targetParam.Content {

internal/application/cpdaily/task/sleepcheck.go

@@ -463,18 +463,15 @@ func (c *CpdailySleepCheckTask) ParseFormJson(ctx context.Context, rawJson map[s
 	}
 	list = append(list, dto)
 
-	var current uint = 1
-
 	if isPhoto := rows["isPhoto"]; isPhoto != nil && isPhoto.Int() == 1 {
 		dto = &formtype.CpTaskFormItem{
 			Title:    "查寝照片",
 			ColName:  "signImg",
 			Type:     formtype.ItemTypeImage,
 			Required: true,
-			Number:   current,
 		}
 		list = append(list, dto)
-		current++
+
 	}
 
 	// 是否范围外签到
@@ -483,7 +480,6 @@ func (c *CpdailySleepCheckTask) ParseFormJson(ctx context.Context, rawJson map[s
 		ColName:  "isMalposition",
 		Type:     formtype.ItemTypeSingle,
 		Required: true,
-		Number:   current,
 		Options: []formtype.CpTaskFormItemOption{
 			{
 				Content:      "是",
@@ -497,7 +493,6 @@ func (c *CpdailySleepCheckTask) ParseFormJson(ctx context.Context, rawJson map[s
 		},
 	}
 	list = append(list, dto)
-	current++
 
 	for key, item := range list {
 		list[key].Show = item.LogicWid == ""

internal/application/recognizer/init.go

@@ -43,15 +43,15 @@ func getOnnxRuntimeName() (onnxRuntimeFileName string, onnxRuntimeFileBytes []by
 	switch systemOS {
 	case "windows":
 		onnxRuntimeFileName = "onnxruntime.dll"
-		onnxRuntimeFileBytes, _ = fs.ReadFile("static/" + onnxRuntimeFileName)
+		onnxRuntimeFileBytes, _ = fs.ReadFile("static/onnxruntime.dll")
 		return
 	case "darwin":
 		onnxRuntimeFileName = "onnxruntime.dylib"
-		onnxRuntimeFileBytes, _ = fs.ReadFile("static/" + onnxRuntimeFileName)
+		onnxRuntimeFileBytes, _ = fs.ReadFile("static/libonnxruntime.1.23.2.dylib")
 		return
 	case "linux":
 		onnxRuntimeFileName = "onnxruntime.so"
-		onnxRuntimeFileBytes, _ = fs.ReadFile("static/" + onnxRuntimeFileName)
+		onnxRuntimeFileBytes, _ = fs.ReadFile("static/libonnxruntime.so.1.23.2")
 		return
 	}
 	logger.Logger.Panic("暂不支持的操作系统：", zap.String("系统名称", systemOS))

internal/application/recognizer/slider/slider_width.go

@@ -0,0 +1,192 @@
+package slider
+
+import (
+	"encoding/base64"
+	"os"
+
+	"gocv.io/x/gocv"
+)
+
+func VerifySliderWidth(bgImgPath, sliderImgPath string) int {
+	// 检查背景图片文件是否存在
+	if _, err := os.Stat(bgImgPath); os.IsNotExist(err) {
+		return -1
+	}
+
+	// 检查滑块图片文件是否存在
+	if _, err := os.Stat(sliderImgPath); os.IsNotExist(err) {
+		return -1
+	}
+
+	// 读取背景图片
+	bgImg := gocv.IMRead(bgImgPath, gocv.IMReadColor)
+	if bgImg.Empty() {
+		return -1
+	}
+	defer bgImg.Close()
+
+	// 读取滑块图片（包含 alpha 通道）
+	sliderImgWithAlpha := gocv.IMRead(sliderImgPath, gocv.IMReadUnchanged)
+	if sliderImgWithAlpha.Empty() {
+		return -1
+	}
+	defer sliderImgWithAlpha.Close()
+
+	// 分离滑块图片的通道
+	channels := gocv.Split(sliderImgWithAlpha)
+	defer func() {
+		for i := range channels {
+			channels[i].Close()
+		}
+	}()
+
+	var sliderImg gocv.Mat
+	var mask gocv.Mat
+
+	// 如果有 alpha 通道（4通道），提取 mask
+	if len(channels) == 4 {
+		// 前3个通道是 BGR
+		sliderImg = gocv.NewMat()
+		defer sliderImg.Close()
+		gocv.Merge(channels[:3], &sliderImg)
+
+		// 使用 alpha 通道作为 mask
+		mask = channels[3].Clone()
+		defer mask.Close()
+	} else if len(channels) == 3 {
+		// 没有透明通道，直接使用原图
+		sliderImg = sliderImgWithAlpha.Clone()
+		defer sliderImg.Close()
+		mask = gocv.NewMat() // 空 mask
+		defer mask.Close()
+	} else {
+		return -1
+	}
+
+	// 创建结果矩阵用于存储匹配结果
+	result := gocv.NewMat()
+	defer result.Close()
+
+	// 直接在原图上使用模板匹配找到滑块位置
+	if mask.Empty() {
+		gocv.MatchTemplate(bgImg, sliderImg, &result, gocv.TmCcoeffNormed, gocv.NewMat())
+	} else {
+		// 带 mask 的模板匹配
+		gocv.MatchTemplate(bgImg, sliderImg, &result, gocv.TmCcoeffNormed, mask)
+	}
+
+	// 找到最佳匹配位置
+	_, maxVal, _, maxLoc := gocv.MinMaxLoc(result)
+
+	// 如果匹配度太低，返回 -1 表示失败
+	if maxVal < 0.6 {
+		return -1
+	}
+
+	// 获取原图上的 x 坐标，然后按比例缩放到目标尺寸
+	originalWidth := bgImg.Cols()
+	targetWidth := 280
+	scale := float64(targetWidth) / float64(originalWidth)
+	scaledX := int(float64(maxLoc.X) * scale)
+
+	// 返回缩放后的 x 坐标（滑块需要移动的距离）
+	return scaledX
+}
+
+// VerifySliderWidthByBase64 通过 base64 编码的图片计算滑块验证码需要移动的距离
+// bgImgBase64: 背景图片的 base64 编码
+// sliderImgBase64: 滑块图片的 base64 编码
+// 返回: 滑块需要移动的 x 距离（已缩放到 280 宽度），失败返回 -1
+func VerifySliderWidthByBase64(bgImgBase64, sliderImgBase64 string) int {
+	// 解码背景图片的 base64
+	bgImgData, err := base64.StdEncoding.DecodeString(bgImgBase64)
+	if err != nil {
+		return -1
+	}
+
+	// 解码滑块图片的 base64
+	sliderImgData, err := base64.StdEncoding.DecodeString(sliderImgBase64)
+	if err != nil {
+		return -1
+	}
+
+	// 从内存中读取背景图片
+	bgImg, err := gocv.IMDecode(bgImgData, gocv.IMReadColor)
+	if err != nil {
+		return -1
+	}
+	if bgImg.Empty() {
+		return -1
+	}
+	defer bgImg.Close()
+
+	// 从内存中读取滑块图片（包含 alpha 通道）
+	sliderImgWithAlpha, err := gocv.IMDecode(sliderImgData, gocv.IMReadUnchanged)
+	if err != nil {
+		return -1
+	}
+	if sliderImgWithAlpha.Empty() {
+		return -1
+	}
+	defer sliderImgWithAlpha.Close()
+
+	// 分离滑块图片的通道
+	channels := gocv.Split(sliderImgWithAlpha)
+	defer func() {
+		for i := range channels {
+			channels[i].Close()
+		}
+	}()
+
+	var sliderImg gocv.Mat
+	var mask gocv.Mat
+
+	// 如果有 alpha 通道（4通道），提取 mask
+	if len(channels) == 4 {
+		// 前3个通道是 BGR
+		sliderImg = gocv.NewMat()
+		defer sliderImg.Close()
+		gocv.Merge(channels[:3], &sliderImg)
+
+		// 使用 alpha 通道作为 mask
+		mask = channels[3].Clone()
+		defer mask.Close()
+	} else if len(channels) == 3 {
+		// 没有透明通道，直接使用原图
+		sliderImg = sliderImgWithAlpha.Clone()
+		defer sliderImg.Close()
+		mask = gocv.NewMat() // 空 mask
+		defer mask.Close()
+	} else {
+		return -1
+	}
+
+	// 创建结果矩阵用于存储匹配结果
+	result := gocv.NewMat()
+	defer result.Close()
+
+	// 直接在原图上使用模板匹配找到滑块位置
+	if mask.Empty() {
+		gocv.MatchTemplate(bgImg, sliderImg, &result, gocv.TmCcoeffNormed, gocv.NewMat())
+	} else {
+		// 带 mask 的模板匹配
+		gocv.MatchTemplate(bgImg, sliderImg, &result, gocv.TmCcoeffNormed, mask)
+	}
+
+	// 找到最佳匹配位置
+	_, maxVal, _, maxLoc := gocv.MinMaxLoc(result)
+
+	// 如果匹配度太低，返回 -1 表示失败
+	if maxVal < 0.6 {
+		return -1
+	}
+
+	// 获取原图上的 x 坐标，然后按比例缩放到目标尺寸
+	originalWidth := bgImg.Cols()
+	targetWidth := 280
+	scale := float64(targetWidth) / float64(originalWidth)
+	scaledX := int(float64(maxLoc.X) * scale)
+
+	// 返回缩放后的 x 坐标（滑块需要移动的距离）
+	return scaledX
+}

internal/framework/schedule/task.go

@@ -2,9 +2,9 @@ package schedule
 
 import (
 	"context"
-	"likedream-goframe/internal/utils"
+	"likedream-goframe/internal/framework/logger"
 
-	"github.com/samber/oops"
+	"go.uber.org/zap"
 )
 
 // StopTask 让任务队列停止执行某任务
@@ -17,5 +17,8 @@ func StopTask(ctx context.Context, queue, taskID string) {
 		queue = "default"
 	}
 	e := globalInspector.DeleteTask(queue, taskID)
-	utils.OkOrPanic(e, oops.WithContext(ctx).With("queue", queue, "taskID", taskID).Wrap)
+	if e != nil {
+		logger.Logger.Error("删除定时任务失败", zap.Error(e))
+	}
+	//utils.OkOrPanic(e, oops.WithContext(ctx).With("queue", queue, "taskID", taskID).Wrap)
 }