feat: Add .env.example configuration file and integrate Redis service into Docker Compose for improved task management. Update desktop application to support document indexing and extraction workflows, enhancing user experience with a new extraction wizard and stepper components. Revise README and documentation for clarity on setup and usage.

services/services-count-facturas-medicas-serving/internal/pipeline/clustering.go

@@ -0,0 +1,112 @@
+package pipeline
+
+import (
+	"math"
+	"sort"
+)
+
+// ClusterRows runs 1D DBSCAN on Y coordinates (parity with sklearn DBSCAN).
+func ClusterRows(boxes []indexedBox, eps float64, minSamples int) {
+	if len(boxes) == 0 {
+		return
+	}
+	ys := make([]float64, len(boxes))
+	for i, b := range boxes {
+		ys[i] = float64(b.Y)
+	}
+	labels := dbscan1D(ys, eps, minSamples)
+	for i := range boxes {
+		boxes[i].Cluster = labels[i]
+	}
+}
+
+func dbscan1D(points []float64, eps float64, minSamples int) []int {
+	n := len(points)
+	labels := make([]int, n)
+	for i := range labels {
+		labels[i] = -1
+	}
+	clusterID := 0
+	visited := make([]bool, n)
+
+	for i := 0; i < n; i++ {
+		if visited[i] {
+			continue
+		}
+		visited[i] = true
+		neighbors := regionQuery(points, i, eps)
+		if len(neighbors) < minSamples {
+			continue
+		}
+		labels[i] = clusterID
+		seed := append([]int(nil), neighbors...)
+		for j := 0; j < len(seed); j++ {
+			q := seed[j]
+			if !visited[q] {
+				visited[q] = true
+				neighborsQ := regionQuery(points, q, eps)
+				if len(neighborsQ) >= minSamples {
+					seed = appendUnique(seed, neighborsQ)
+				}
+			}
+			if labels[q] == -1 {
+				labels[q] = clusterID
+			}
+		}
+		clusterID++
+	}
+	return labels
+}
+
+func regionQuery(points []float64, idx int, eps float64) []int {
+	var neighbors []int
+	for i, p := range points {
+		if math.Abs(p-points[idx]) <= eps {
+			neighbors = append(neighbors, i)
+		}
+	}
+	return neighbors
+}
+
+func appendUnique(seed, add []int) []int {
+	inSeed := make(map[int]bool, len(seed))
+	for _, v := range seed {
+		inSeed[v] = true
+	}
+	for _, v := range add {
+		if !inSeed[v] {
+			seed = append(seed, v)
+			inSeed[v] = true
+		}
+	}
+	return seed
+}
+
+type indexedBox struct {
+	Text    string
+	X       int
+	Y       int
+	W       int
+	H       int
+	Cluster int
+}
+
+func groupByCluster(boxes []indexedBox) map[int][]indexedBox {
+	groups := make(map[int][]indexedBox)
+	for _, b := range boxes {
+		if b.Cluster < 0 {
+			continue
+		}
+		groups[b.Cluster] = append(groups[b.Cluster], b)
+	}
+	return groups
+}
+
+func sortClusters(groups map[int][]indexedBox) []int {
+	keys := make([]int, 0, len(groups))
+	for k := range groups {
+		keys = append(keys, k)
+	}
+	sort.Ints(keys)
+	return keys
+}