package imageproc

import (
	"fmt"
	"image"

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

func GTiffToJPG(ftiff, fjpg string) 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))
	if len(bands) < 3 {
		err = fmt.Errorf("TIFF file %s has less than 3 bands", ftiff)
		log.Error(err)
		return err
	}

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

	// 读取每个波段并转换为 8 位
	img := gocv.NewMatWithSize(height, width, gocv.MatTypeCV16UC3)
	for i := 1; i <= 3; i++ {
		band := ds.Bands()[i-1]
		data := make([]uint16, width*height)
		err = band.Read(0, 0, data, width, height)
		if err != nil {
			log.Printf("Error reading band %d: %v", i, err)
			return err
		}

		// 计算最小值和最大值
		var minVal, maxVal uint16 = 65535, 0
		for _, value := range data {
			if value < minVal {
				minVal = value
			}
			if value > maxVal {
				maxVal = value
			}
		}

		// 将 16 位数据缩放到 8 位并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]
				scaledValue := uint8(float64(value-minVal) / float64(maxVal-minVal) * 255)
				img.SetUCharAt(y, x*3+(i-1), scaledValue)
			}
		}

		// 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*3+(i-1), int16(value))
		// 	}
		// }
	}

	// 调整图像大小
	resizedImg := gocv.NewMat()
	gocv.Resize(img, &resizedImg, image.Point{X: 2336, Y: 2336}, 0, 0, gocv.InterpolationCubic)

	// 保存为 JPG 文件
	ok := gocv.IMWrite(fjpg, resizedImg)
	if !ok {
		err = fmt.Errorf("error saving %s", fjpg)
		return err
	}

	return nil
}