refactor(cv): extract generic box resolution to domain layer

Introduce GenericBoxResolver to process generic_box detections and update YOLO labels.

Author: jatezzz

cv-image-to-xml/src/main/assets/best_float32.tflite

@@ -1,11 +1,11 @@
-dropdown
+generic_box
+dropdown_symbol
 image_placeholder
 button
 checkbox_checked
+checkbox_unchecked
 radio_button_unchecked
 radio_button_checked
-text_entry_box
-checkbox_unchecked
 slider
 switch_off
 switch_on

cv-image-to-xml/src/main/assets/labels.txt

@@ -10,6 +10,7 @@ import org.appdevforall.codeonthego.computervision.domain.model.DetectionResult
 import com.google.mlkit.vision.text.Text
 import kotlinx.coroutines.Dispatchers
 import kotlinx.coroutines.withContext
+import org.appdevforall.codeonthego.computervision.domain.GenericBoxResolver
 
 class ComputerVisionRepositoryImpl(
     private val assetManager: AssetManager,
@@ -26,7 +27,8 @@ class ComputerVisionRepositoryImpl(
     override suspend fun runYoloInference(bitmap: Bitmap): Result<List<DetectionResult>> =
         withContext(Dispatchers.Default) {
             runCatching {
-                yoloModelSource.runInference(bitmap)
+                val rawDetections = yoloModelSource.runInference(bitmap)
+                GenericBoxResolver().resolve(rawDetections)
             }
         }
 

cv-image-to-xml/src/main/java/org/appdevforall/codeonthego/computervision/data/repository/ComputerVisionRepositoryImpl.kt

@@ -0,0 +1,37 @@
+package org.appdevforall.codeonthego.computervision.domain
+
+import android.graphics.RectF
+import org.appdevforall.codeonthego.computervision.domain.model.DetectionResult
+import kotlin.math.hypot
+
+class GenericBoxResolver {
+
+    fun resolve(detections: List<DetectionResult>): List<DetectionResult> {
+        val dropdownSymbols = detections.filter { it.label == "dropdown_symbol" }
+
+        return detections.mapNotNull { det ->
+            when (det.label) {
+                "dropdown_symbol" -> null
+                "generic_box" -> {
+                    val hasSymbolNearby = dropdownSymbols.any { symbol ->
+                        isNearby(det.boundingBox, symbol.boundingBox, 0.8f)
+                    }
+                    det.copy(label = if (hasSymbolNearby) "dropdown" else "text_entry_box")
+                }
+                else -> det
+            }
+        }
+    }
+
+    private fun isNearby(box1: RectF, box2: RectF, thresholdFactor: Float = 1.5f): Boolean {
+        val avgDim1 = (box1.width() + box1.height()) / 2f
+        val distanceThreshold = thresholdFactor * avgDim1
+
+        val distance = hypot(
+            (box1.centerX() - box2.centerX()).toDouble(),
+            (box1.centerY() - box2.centerY()).toDouble()
+        ).toFloat()
+
+        return distance < distanceThreshold
+    }
+}