save Tmat in binary format

pkg/rrc/rrc.go

@@ -4,6 +4,7 @@ import (
 	"bufio"
 	"fmt"
 	"os"
+	"sync"
 
 	log "github.com/sirupsen/logrus"
 	"gocv.io/x/gocv"
@@ -52,30 +53,57 @@ func (rrc *RRC) StatisticalPAN(dsfile string) error {
 	defer f.Close()
 
 	scanner := bufio.NewScanner(f)
+	var files []string
 	for scanner.Scan() {
-		l0 := scanner.Text()
-		log.Println("statistical PAN RAW: ", l0)
-		data, err := os.ReadFile(l0)
-		if err != nil {
-			log.Error("Error reading file: ", err)
-			continue
-		}
-
-		height := len(data) / (PANCameraProbeNum * 2)
-		img, err := gocv.NewMatFromBytes(height, PANCameraProbeNum, gocv.MatTypeCV16U, data)
-		if err != nil {
-			log.Error("Error creating Mat from bytes: ", err)
-			return err
-		}
-
-		rrc.Histograms[0].statistical(img)
-		img.Close()
+		files = append(files, scanner.Text())
 	}
 
+	// 并发处理
+	var wg sync.WaitGroup
+	jobs := make(chan struct{}, 5)
+	var hists []*ProbeHistogram
+	var mutex sync.Mutex
+	for _, file := range files {
+		wg.Add(1)
+		go func(l0 string) {
+			defer wg.Done()
+
+			jobs <- struct{}{}
+			defer func() { <-jobs }()
+
+			log.Println("statistical PAN RAW: ", l0)
+			data, err := os.ReadFile(l0)
+			if err != nil {
+				log.Error("Error reading file: ", err)
+				return
+			}
+
+			height := len(data) / (PANCameraProbeNum * 2)
+			img, err := gocv.NewMatFromBytes(height, PANCameraProbeNum, gocv.MatTypeCV16U, data)
+			if err != nil {
+				log.Error("Error creating Mat from bytes: ", err)
+				return
+			}
+
+			var hist ProbeHistogram
+			hist.init(PANCameraProbeNum)
+			hist.statistical(img)
+			img.Close()
+
+			mutex.Lock()
+			hists = append(hists, &hist)
+			mutex.Unlock()
+
+		}(file)
+	}
+
+	wg.Wait()
+	log.Println("sum PAN histogram...")
+	rrc.Histograms[0].sum(hists)
 	log.Println("compute PAN histogram...")
 	rrc.Histograms[0].compute()
 	log.Println("save PAN gray table matrix.")
-	rrc.Histograms[0].save("data/rrc/pan_gray_table.dat")
+	rrc.Histograms[0].saveLUT("data/rrc/B0.LUT")
 
 	return nil
 }
@@ -88,43 +116,68 @@ func (rrc *RRC) StatisticalMSS(dsfile string) error {
 	defer f.Close()
 
 	scanner := bufio.NewScanner(f)
+
+	var files []string
 	for scanner.Scan() {
-		l0 := scanner.Text()
-		log.Println("statistical MSS RAW: ", l0)
-		data, err := os.ReadFile(l0)
-		if err != nil {
-			log.Error("Error reading file: ", err)
-			continue
-		}
-
-		width := MSSCameraProbeNum
-		height := len(data) / (width * 2)
-		mssData := make([][]byte, 4)
-		for h := 0; h < height; h++ {
-			row := data[h*width*4*2 : (h+1)*width*4*2]
-			for i := 0; i < 4; i++ {
-				mssData[i] = append(mssData[i], row[i*width*2:(i+1)*width*2]...)
-			}
-		}
-
-		var mssImages [4]gocv.Mat
-		for i := 0; i < 4; i++ {
-			mssImages[i], err = gocv.NewMatFromBytes(height, width, gocv.MatTypeCV16U, mssData[i])
-			if err != nil {
-				log.Error("Error creating Mat from bytes: ", err)
-				return err
-			}
-
-			rrc.Histograms[i+1].statistical(mssImages[i])
-			mssImages[i].Close()
-		}
+		files = append(files, scanner.Text())
 	}
 
+	var wg sync.WaitGroup
+	jobs := make(chan struct{}, 5)
+	var hists [4][]*ProbeHistogram
+	var mutex sync.Mutex
+	for _, file := range files {
+		wg.Add(1)
+		go func(l0 string) {
+			defer wg.Done()
+			jobs <- struct{}{}
+			defer func() { <-jobs }()
+
+			log.Println("statistical MSS RAW: ", l0)
+			data, err := os.ReadFile(l0)
+			if err != nil {
+				log.Error("Error reading file: ", err)
+				return
+			}
+
+			width := MSSCameraProbeNum
+			height := len(data) / (width * 2)
+			mssData := make([][]byte, 4)
+			for h := 0; h < height; h++ {
+				row := data[h*width*4*2 : (h+1)*width*4*2]
+				for i := 0; i < 4; i++ {
+					mssData[i] = append(mssData[i], row[i*width*2:(i+1)*width*2]...)
+				}
+			}
+
+			var mssImages [4]gocv.Mat
+			for i := 0; i < 4; i++ {
+				mssImages[i], err = gocv.NewMatFromBytes(height, width, gocv.MatTypeCV16U, mssData[i])
+				if err != nil {
+					log.Error("Error creating Mat from bytes: ", err)
+					return
+				}
+
+				var hist ProbeHistogram
+				hist.init(PANCameraProbeNum)
+				hist.statistical(mssImages[i])
+				mssImages[i].Close()
+
+				mutex.Lock()
+				hists[i] = append(hists[i], &hist)
+				mutex.Unlock()
+			}
+		}(file)
+	}
+
+	wg.Wait()
 	for i := 1; i < 5; i++ {
+		log.Println("sum MSS histogram...")
+		rrc.Histograms[i].sum(hists[i-1])
 		log.Println("compute MSS histogram...")
 		rrc.Histograms[i].compute()
 		log.Println("save MSS gray table matrix.")
-		rrc.Histograms[i].save(fmt.Sprintf("data/rrc/mss%d_gray_table.dat", i))
+		rrc.Histograms[i].saveLUT(fmt.Sprintf("data/rrc/B%d.LUT", i))
 	}
 
 	return nil