package imageproc

import (
	"fmt"
	"image"

	"github.com/airbusgeo/godal"
	log "github.com/sirupsen/logrus"
	"gocv.io/x/gocv"
)

func GTiffToJPG(ftiff, fjpg string, reversed bool) error {
	// 打开 TIFF 文件
	ds, err := godal.Open(ftiff)
	if err != nil {
		log.Printf("Error opening TIFF file %s: %v", ftiff, err)
		return err
	}
	defer ds.Close()

	bands := ds.Bands()
	log.Infof("TIFF file %s has %d bands", ftiff, len(bands))

	// 获取图像大小
	width := bands[0].Structure().SizeX
	height := bands[0].Structure().SizeY
	bandsCnt := len(bands)

	// 创建 16 位图像矩阵
	var img gocv.Mat
	defer img.Close()
	if bandsCnt == 1 {
		img = gocv.NewMatWithSize(height, width, gocv.MatTypeCV16UC1)
	} else {
		bandsCnt = 3 // 只取前三个波段
		img = gocv.NewMatWithSize(height, width, gocv.MatTypeCV16UC3)
	}

	// 读取每个波段并存储到图像矩阵中
	for i := 0; i < bandsCnt; i++ {
		band := bands[i]
		data := make([]uint16, width*height)
		err = band.Read(0, 0, data, width, height)
		if err != nil {
			fmt.Printf("Error reading band %d: %v\n", i, err)
			return err
		}

		// 将 16 位数据存储到图像的相应通道
		for y := 0; y < height; y++ {
			for x := 0; x < width; x++ {
				value := data[y*width+x]
				img.SetShortAt(y, x*bandsCnt+i, int16(value))
			}
		}
	}

	// 重采样图像
	gocv.Resize(img, &img, image.Point{X: img.Cols() / 2, Y: img.Rows() / 2}, 0, 0, gocv.InterpolationCubic)

	// 创建 8 位图像矩阵
	img8 := gocv.NewMat()
	defer img8.Close()
	if bandsCnt == 1 {
		img.ConvertToWithParams(&img8, gocv.MatTypeCV8UC1, 1.0/256.0*2, 0)
	} else {
		img.ConvertToWithParams(&img8, gocv.MatTypeCV8UC3, 1.0/256.0*2, 0)
		if reversed {
			channels := gocv.Split(img8)
			gocv.Merge([]gocv.Mat{channels[2], channels[1], channels[0]}, &img8)
			for _, ch := range channels {
				ch.Close()
			}
		}
	}

	ok := gocv.IMWrite(fjpg, img8)
	if !ok {
		err = fmt.Errorf("error saving %s", fjpg)
		return err
	}

	return nil
}