wait to test

core/function-impl/mogo-core-function-map/src/main/java/com/mogo/eagle/core/function/map/IdentifyDataDrawer.java

@@ -1,11 +1,13 @@
 package com.mogo.eagle.core.function.map;
 
+import static com.mogo.eagle.core.utilcode.mogo.logger.scene.SceneConstant.M_HMI;
+
+import android.annotation.SuppressLint;
 import android.content.Context;
 
 import com.mogo.commons.AbsMogoApplication;
 import com.mogo.eagle.core.data.config.FunctionBuildConfig;
 import com.mogo.eagle.core.data.enums.TrafficTypeEnum;
-import com.mogo.eagle.core.data.traffic.TrafficData;
 import com.mogo.eagle.core.utilcode.mogo.logger.CallerLogger;
 import com.mogo.eagle.core.utilcode.util.UiThreadHandler;
 import com.mogo.map.MogoMarkerManager;
@@ -31,12 +33,12 @@ public class IdentifyDataDrawer {
     /**
      * 上一帧数据的缓存
      */
-    private static final ConcurrentHashMap<String, TrafficData> mMarkersCaches = new ConcurrentHashMap<>();
+    private static final ConcurrentHashMap<String, MessagePad.TrackedObject> mMarkersCaches = new ConcurrentHashMap<>();
 
     /**
      * 已经感知不到的脏数据
      */
-    private final ConcurrentHashMap<String, TrafficData> mDirtyPositions = new ConcurrentHashMap<>();
+    private final ConcurrentHashMap<String, MessagePad.TrackedObject> firstData = new ConcurrentHashMap<>();
     /**
      * 记录每次实际绘制的交通元素UUID
      */
@@ -71,6 +73,7 @@ public class IdentifyDataDrawer {
      *
      * @param resultList adas感知融合数据
      */
+    @SuppressLint("NewApi")
     public void renderAdasRecognizedResult(List<MessagePad.TrackedObject> resultList) {
         if (resultList == null || resultList.isEmpty()) {
             clearOldMarker();
@@ -84,35 +87,26 @@ public class IdentifyDataDrawer {
             return;
         }
 
-        // 循环将集合中的数据提取记录
-
-        for (MessagePad.TrackedObject trafficData : resultList) {
-            // 过滤掉未知感知数据
-            if (!FunctionBuildConfig.isDrawUnknownIdentifyData &&
-                    trafficData.getType() == TrafficTypeEnum.TYPE_TRAFFIC_ID_WEI_ZHI.getType()) {
-                //CallerLogger.INSTANCE.w(TAG, "未知感知类型数据，丢弃，不渲染");
-                continue;
+        //清除缓存
+        for (MessagePad.TrackedObject data : resultList) {
+            if(trafficDataUuidList.size() > 0 && trafficDataUuidList.contains("" + data.getUuid())){
+                trafficDataUuidList.remove(data.getUuid());
             }
-            trafficDataUuidList.add("" + trafficData.getUuid());
         }
-//        // 找出上一针数据中已经不在本次数据中存在的数据
-//        for (String uuid : mMarkersCaches.keySet()) {
-//            if (!trafficDataUuidList.contains(uuid)) {
-//                mDirtyPositions.put(uuid, mMarkersCaches.get(uuid));
-//            }
-//        }
-//        // 移除脏数据
-//        for (String uuid : mDirtyPositions.keySet()) {
-//            MogoApisHandler.getInstance().getApis()
-//                    .getMapServiceApi()
-//                    .getMarkerManager(mContext)
-//                    .removeMarker(uuid);
-//        }
-
-        // 绘制新数据
-        MogoMarkerManager.getInstance(mContext)
-                .updateBatchMarkerPosition(filterTrafficData(resultList));
+        trafficDataUuidList.forEach(uuid -> {
+            mMarkersCaches.remove(uuid);
+        });
 
+        CallerLogger.INSTANCE.d(M_HMI + "arrow47", "origin data size : " + resultList.size());
+        ArrayList<MessagePad.TrackedObject> filterList = filterTrafficData(resultList);
+        if (filterList.size() > 0) {
+            // 绘制新数据
+            MogoMarkerManager.getInstance(mContext)
+                    .updateBatchMarkerPosition(filterList);
+        }
+        CallerLogger.INSTANCE.d(M_HMI + "arrow47", "first data size  : " + firstData.size() + " , mMarkersCaches : " + mMarkersCaches.size());
+        // 首次未添加的感知物在调用完绘制方法后再塞入cache map
+        mMarkersCaches.putAll(firstData);
     }
 
     /**
@@ -121,14 +115,39 @@ public class IdentifyDataDrawer {
      * @return 过滤后的数据集合
      */
     private ArrayList<MessagePad.TrackedObject> filterTrafficData(List<MessagePad.TrackedObject> trafficData) {
+        firstData.clear();
         mFilterTrafficData.clear();
+        trafficDataUuidList.clear();
         for (MessagePad.TrackedObject data : trafficData) {
             // 过滤掉未知感知数据
-            if (data.getType() == TrafficTypeEnum.TYPE_TRAFFIC_ID_WEI_ZHI.getType()) {
+            if (!FunctionBuildConfig.isDrawUnknownIdentifyData && data.getType() == TrafficTypeEnum.TYPE_TRAFFIC_ID_WEI_ZHI.getType()) {
                 //CallerLogger.INSTANCE.w(TAG, "未知感知类型数据，丢弃，不渲染");
                 continue;
             }
-            mFilterTrafficData.add(data);
+
+            //首次过来的数据不添加,首次未添加的感知物在调用完绘制方法后再塞入cache map
+            MessagePad.TrackedObject cacheData = mMarkersCaches.get("" + data.getUuid());
+            if (cacheData != null) {
+                //todo 测试航向角修正时打开
+                MessagePad.TrackedObject correctData = null;
+                //todo 判断点是不是在当前车道线上，如果是，判断差值，进行修正
+//                if (Math.abs(cacheData.getHeading() - data.getHeading()) > 90) {
+//                    CallerLogger.INSTANCE.d(M_HMI + "arrow47","uuid修正 上一帧 : " + cacheData.getHeading() + " , 当前帧 : " + data.getHeading());
+//                    correctData = data.toBuilder().setHeading(cacheData.getHeading()).build();
+//                }
+                if (correctData != null) {
+                    mFilterTrafficData.add(correctData);
+                    //更新已存在的感知物体数据
+                    mMarkersCaches.put("" + data.getUuid(), correctData);
+                } else {
+                    mFilterTrafficData.add(data);
+                    //更新已存在的感知物体数据
+                    mMarkersCaches.put("" + data.getUuid(), data);
+                }
+            } else {
+                firstData.put("" + data.getUuid(), data);
+            }
+            trafficDataUuidList.add("" + data.getUuid());
         }
         return mFilterTrafficData;
     }