Fix/classification streaming support

android/src/main/kotlin/com/ultralytics/yolo/YOLOPlugin.kt

@@ -297,14 +297,18 @@ class YOLOPlugin : FlutterPlugin, ActivityAware, MethodChannel.MethodCallHandler
             }
             YOLOTask.CLASSIFY -> {
               yoloResult.probs?.let { probs ->
-                // Build top5 list safely using zip to handle mismatched list lengths
-                // Convert top5Confs to List to ensure Iterable compatibility (may be FloatArray)
-                val top5List = probs.top5Labels.zip(probs.top5Confs.toList()).map { (name, conf) ->
-                  mapOf(
-                    "name" to name,
-                    "confidence" to conf.toDouble()
-                  )
-                }
+                // Build top5 list with labels and confidence only
+                // Omit class field to maintain consistency across platforms
+                // (iOS native API doesn't provide top5 indices)
+                val top5List = probs.top5Labels
+                  .zip(probs.top5Confs.toList())
+                  .take(5)
+                  .map { (name, conf) ->
+                    mapOf(
+                      "name" to name,
+                      "confidence" to conf.toDouble()
+                    )
+                  }
 
                 // Classification response following Results.summary() format
                 // Reference: https://docs.ultralytics.com/reference/engine/results/
@@ -319,8 +323,9 @@ class YOLOPlugin : FlutterPlugin, ActivityAware, MethodChannel.MethodCallHandler
                 response["boxes"] = listOf(
                   mapOf(
                     "class" to probs.top1Index,
-                    "className" to probs.top1Label,
+                    "name" to probs.top1Label,
                     "classIndex" to probs.top1Index,
+                    "className" to probs.top1Label,
                     "confidence" to probs.top1Conf.toDouble(),
                     "x1" to 0.0,
                     "y1" to 0.0,

android/src/main/kotlin/com/ultralytics/yolo/YOLOView.kt

@@ -1712,6 +1712,50 @@ class YOLOView @JvmOverloads constructor(
             map["detections"] = detections
             Log.d(TAG, "✅ Total detections in stream: ${detections.size} (boxes: ${result.boxes.size}, obb: ${result.obb.size})")
         }
+
+        // Add classification results (if available and enabled for CLASSIFY task)
+        if (config.includeClassifications && result.probs != null) {
+            val probs = result.probs!!
+
+            val top5List = probs.top5Labels
+              .zip(probs.top5Confs.toList())
+              .take(5)
+              .map { (name, conf) ->
+                mapOf(
+                  "name" to name,
+                  "confidence" to conf.toDouble()
+                )
+              }
+
+            // Add classification result to detections array (for compatibility with YOLOResult.fromMap)
+            val detections = (map["detections"] as? List<Map<String, Any>>)?.toMutableList() ?: ArrayList()
+
+            val classificationDetection = HashMap<String, Any>()
+            // Omit class field from streaming to maintain consistency with iOS
+            // (iOS native API doesn't provide class index)
+            classificationDetection["name"] = probs.top1Label
+            classificationDetection["confidence"] = probs.top1Conf.toDouble()
+            classificationDetection["top5"] = top5List
+
+            // Full image bounding box for classification
+            val boundingBox = HashMap<String, Any>()
+            boundingBox["left"] = 0.0
+            boundingBox["top"] = 0.0
+            boundingBox["right"] = result.origShape.width.toDouble()
+            boundingBox["bottom"] = result.origShape.height.toDouble()
+            classificationDetection["boundingBox"] = boundingBox
+
+            // Normalized bounding box (full image)
+            val normalizedBox = HashMap<String, Any>()
+            normalizedBox["left"] = 0.0
+            normalizedBox["top"] = 0.0
+            normalizedBox["right"] = 1.0
+            normalizedBox["bottom"] = 1.0
+            classificationDetection["normalizedBox"] = normalizedBox
+
+            detections.add(classificationDetection)
+            map["detections"] = detections
+        }
 
         // Add performance metrics (if enabled)
         if (config.includeProcessingTimeMs) {

ios/Classes/YOLOView.swift

@@ -1768,6 +1768,56 @@ extension YOLOView: AVCapturePhotoCaptureDelegate {
       map["detections"] = detections
     }
 
+    // Add classification results (if available and enabled for CLASSIFY task)
+    if config.includeClassifications, let probs = result.probs, result.boxes.isEmpty {
+      // Get or create detections array (for compatibility with YOLOResult deserialization)
+      var detections = map["detections"] as? [[String: Any]] ?? []
+
+      // Build top5 list with labels and confidence
+      // Note: iOS native API doesn't provide top5 indices, so we omit class field
+      // to maintain consistency with Android when indices are unavailable
+      var top5List: [[String: Any]] = []
+      let top5Labels = probs.top5Labels
+      let top5Confs = probs.top5Confs
+
+      for i in 0..<min(top5Labels.count, top5Confs.count) {
+        top5List.append([
+          "name": top5Labels[i],
+          "confidence": Double(top5Confs[i])
+        ])
+      }
+
+      // Create single detection object with top1 and top5 info
+      var detection: [String: Any] = [:]
+
+      // Note: iOS native API doesn't provide real class index, so we omit it
+      // to avoid sending potentially incorrect values (e.g., -1 or wrong index)
+      detection["name"] = probs.top1Label
+      detection["confidence"] = Double(probs.top1Conf)
+      detection["top5"] = top5List
+
+      // Classification doesn't have bounding boxes, use full image bounds
+      let boundingBox: [String: Any] = [
+        "left": 0.0,
+        "top": 0.0,
+        "right": Double(result.orig_shape.width),
+        "bottom": Double(result.orig_shape.height)
+      ]
+      detection["boundingBox"] = boundingBox
+
+      // Normalized bounding box (full image)
+      let normalizedBox: [String: Any] = [
+        "left": 0.0,
+        "top": 0.0,
+        "right": 1.0,
+        "bottom": 1.0
+      ]
+      detection["normalizedBox"] = normalizedBox
+
+      detections.append(detection)
+      map["detections"] = detections
+    }
+
     // Add performance metrics (if enabled)
     if config.includeProcessingTimeMs {
       map["processingTimeMs"] = result.speed * 1000