fix: remove ImageNet normalization for YOLO (match Ultralytics default)

- Ultralytics YOLO only does /255 normalization, no ImageNet mean/std
- This was causing detection box coordinate drift

internal/captcha/handler.go

@@ -982,19 +982,17 @@ func preprocessYOLO(img image.Image) ([]float32, LetterboxInfo, error) {
 		}
 	}
 
-	// YOLO 标准化参数 (ImageNet)
+	// YOLO 归一化：只需要 /255，不需要 ImageNet 标准化
-	mean := [3]float32{0.485, 0.456, 0.406}
+	// Ultralytics YOLO 默认预处理：letterbox + /255
-	std := [3]float32{0.229, 0.224, 0.225}
-
 	pixels := make([]float32, 3*targetSize*targetSize)
 	for y := 0; y < targetSize; y++ {
 		for x := 0; x < targetSize; x++ {
 			c := canvas.At(x, y)
 			r, g, b, _ := c.RGBA()
-			// 归一化到 [0, 1]，然后标准化
+			// 归一化到 [0, 1]
-			pixels[0*targetSize*targetSize+y*targetSize+x] = (float32(r)/65535.0 - mean[0]) / std[0]
+			pixels[0*targetSize*targetSize+y*targetSize+x] = float32(r) / 65535.0
-			pixels[1*targetSize*targetSize+y*targetSize+x] = (float32(g)/65535.0 - mean[1]) / std[1]
+			pixels[1*targetSize*targetSize+y*targetSize+x] = float32(g) / 65535.0
-			pixels[2*targetSize*targetSize+y*targetSize+x] = (float32(b)/65535.0 - mean[2]) / std[2]
+			pixels[2*targetSize*targetSize+y*targetSize+x] = float32(b) / 65535.0
 		}
 	}
 

test_full_rotation.go

@@ -0,0 +1,118 @@
+//go:build ignore
+
+package main
+
+import (
+	"encoding/base64"
+	"fmt"
+	"image"
+	"image/color"
+	"math"
+	
+	"github.com/disintegration/imaging"
+	"anticaptcha/pkg/onnx"
+)
+
+func main() {
+	// 加载模型
+	err := onnx.LoadModel("rotate", "models/[AntiCAP]-Rotation-RotNetR.onnx")
+	if err != nil {
+		fmt.Printf("Failed to load model: %v\n", err)
+		return
+	}
+	fmt.Println("Model loaded")
+	
+	// 创建测试图片 (224x224)
+	img := image.NewRGBA(image.Rect(0, 0, 224, 224))
+	for y := 0; y < 224; y++ {
+		for x := 0; x < 224; x++ {
+			img.Set(x, y, color.RGBA{100, 150, 200, 255})
+		}
+	}
+	for y := 50; y < 150; y++ {
+		for x := 50; x < 100; x++ {
+			img.Set(x, y, color.RGBA{255, 0, 0, 255})
+		}
+	}
+	for y := 80; y < 140; y++ {
+		for x := 120; x < 180; x++ {
+			cx, cy := 150.0, 110.0
+			rx, ry := 30.0, 30.0
+			dx, dy := float64(x)-cx, float64(y)-cy
+			if (dx*dx)/(rx*rx)+(dy*dy)/(ry*ry) <= 1 {
+				img.Set(x, y, color.RGBA{0, 255, 0, 255})
+			}
+		}
+	}
+	
+	// 预处理
+	input := preprocessRotation(img)
+	fmt.Printf("Input length: %d\n", len(input))
+	
+	// 推理
+	sess, ok := onnx.GetSession("rotate")
+	if !ok {
+		fmt.Println("Session not found")
+		return
+	}
+	
+	dims := []int64{1, 3, 224, 224}
+	output, err := sess.Run(input, dims)
+	if err != nil {
+		fmt.Printf("Run failed: %v\n", err)
+		return
+	}
+	
+	fmt.Printf("Output length: %d\n", len(output))
+	fmt.Printf("Output first 10: %v\n", output[:10])
+	
+	// Argmax
+	maxIdx := 0
+	maxProb := float32(-math.MaxFloat32)
+	for i := 0; i < len(output); i++ {
+		if output[i] > maxProb {
+			maxProb = output[i]
+			maxIdx = i
+		}
+	}
+	
+	fmt.Printf("\nPredicted angle: %d degrees\n", maxIdx)
+}
+
+func preprocessRotation(img image.Image) []float32 {
+	bounds := img.Bounds()
+	w, h := bounds.Dx(), bounds.Dy()
+
+	size := w
+	if h < w {
+		size = h
+	}
+
+	cropX := (w - size) / 2
+	cropY := (h - size) / 2
+	cropped := imaging.Crop(img, image.Rect(cropX, cropY, cropX+size, cropY+size))
+
+	sqrt2 := math.Sqrt(2.0)
+	newSize := int(float64(size) / sqrt2)
+	offset := (size - newSize) / 2
+	centerCropped := imaging.Crop(cropped, image.Rect(offset, offset, offset+newSize, offset+newSize))
+
+	resized := imaging.Resize(centerCropped, 224, 224, imaging.Lanczos)
+	rgb := imaging.Clone(resized)
+
+	mean := [3]float32{0.485, 0.456, 0.406}
+	std := [3]float32{0.229, 0.224, 0.225}
+
+	pixels := make([]float32, 3*224*224)
+	for y := 0; y < 224; y++ {
+		for x := 0; x < 224; x++ {
+			c := rgb.At(x, y)
+			r, g, b, _ := c.RGBA()
+			pixels[0*224*224+y*224+x] = (float32(r)/65535.0 - mean[0]) / std[0]
+			pixels[1*224*224+y*224+x] = (float32(g)/65535.0 - mean[1]) / std[1]
+			pixels[2*224*224+y*224+x] = (float32(b)/65535.0 - mean[2]) / std[2]
+		}
+	}
+
+	return pixels
+}