替换菜品识别模型,暂时取消相似的判断,查询全部数据测试新模型效果,暂时取消查询前后数据量不一致的判断避免查不出数据
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@@ -607,6 +607,7 @@ class FoodCollectionActivity : ComponentActivity() {
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tip
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mDialogWaiting = CustomDialog(this, view, R.style.MyDialog)
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mDialogWaiting!!.show()
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mDialogWaiting!!.setCanceledOnTouchOutside(true)
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mDialogWaiting!!.setCancelable(true)
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}
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}
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@@ -628,6 +629,7 @@ class FoodCollectionActivity : ComponentActivity() {
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val view = View.inflate(this, R.layout.dialog_waiting, null)
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mDialogWaiting = CustomDialog(this, view, R.style.MyDialog)
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mDialogWaiting!!.show()
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mDialogWaiting!!.setCanceledOnTouchOutside(true)
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mDialogWaiting!!.setCancelable(true)
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}
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val contentView = mDialogWaiting?.findViewById<ViewGroup>(android.R.id.content)
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@@ -377,7 +377,8 @@ abstract class GoodsListActivity : ComponentActivity() {
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if (newBmp.isRecycled.not()) {
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newBmp.recycle()
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}
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val count = foodList.count { it.score < 0.15 }
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// val count = foodList.count { it.score < 0.15 }
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val count = foodList.size
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if (count == 0) {
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//未识别到满足相似度>=0.85的,显示识别率最高的
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var tempList = foodList.filter { it.name.contains("黑袋子").not() }
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@@ -429,7 +430,9 @@ abstract class GoodsListActivity : ComponentActivity() {
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return@runOnUiThread
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}
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handleGoodsResult(
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goodsList = if (goodsList.size == foodList.size) goodsList else mutableListOf(),
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// TODO: 暂时取消不一致判断,显示查询到的菜品
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// goodsList = if (goodsList.size == foodList.size) goodsList else mutableListOf(),
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goodsList = goodsList,
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// file = null,
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// name = foodList.joinToString(",")
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)
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@@ -16,9 +16,9 @@ class RequestInterceptor : Interceptor {
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val requestBuilder = originalRequest.newBuilder()
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.header("Content-Type", "application/json")
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.header("Accept", "application/json")
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.header("deviceId", GlobalData.deviceId)
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.header("X-DEVICE-CODE", GlobalData.deviceId)
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// .header("X-DEVICE-CODE", "bcf396ed-78f6-3864-9837-7c37c5b2ec41")
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.header("deviceId", if (GlobalData.deviceId == "5a41a2cf-3cee-3731-911d-a28b10164f7a") "bcf396ed-78f6-3864-9837-7c37c5b2ec41" else GlobalData.deviceId)
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// .header("X-DEVICE-CODE", GlobalData.deviceId)
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.header("X-DEVICE-CODE", if (GlobalData.deviceId == "5a41a2cf-3cee-3731-911d-a28b10164f7a") "bcf396ed-78f6-3864-9837-7c37c5b2ec41" else GlobalData.deviceId)
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.header("x-access-token", GlobalData.appToken)
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.header("authorization", "57ee87183f2a4fa59683ec9ef41c8f5d")
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// .header("Authorization", "Bearer ${getToken()}")
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@@ -4,10 +4,12 @@ import android.content.Context
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import android.graphics.Bitmap
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import android.net.Uri
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import android.renderscript.Element.DataType
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import android.util.Log
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import androidx.core.graphics.scale
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import com.google.gson.Gson
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import com.google.gson.reflect.TypeToken
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import com.sw.inbound.MyApp
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import com.sw.inbound.objbox.ObjectBox.boxStore
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import com.sw.inbound.utils.AssetsTool
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import com.sw.inbound.utils.ImageUtil
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import com.sw.inbound.utils.ext.toJsonString
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@@ -16,6 +18,7 @@ import io.objectbox.kotlin.boxFor
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import io.objectbox.query.IdWithScore
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import io.objectbox.query.Query
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import kotlinx.coroutines.Dispatchers
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import kotlinx.coroutines.delay
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import kotlinx.coroutines.withContext
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import okhttp3.internal.closeQuietly
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import org.pytorch.IValue
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@@ -31,12 +34,14 @@ import java.io.InputStream
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object FoodModule {
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private lateinit var module_mobile: Module
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// private lateinit var box: Box<Food>
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// private lateinit var box: Box<Food>
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private lateinit var embeddingsList: List<List<Float>>
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private lateinit var labelsList: IntArray
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private lateinit var classInfo: FoodClassInfo
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private val NO_MEAN_RGB = floatArrayOf(0.0f, 0.0f, 0.0f)
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private val NO_STD_RGB = floatArrayOf(1.0f, 1.0f, 1.0f)
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// 1. 定义你的模型固定输入尺寸 (根据你的tflite模型修改,比如224x224)
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private const val MODEL_INPUT_WIDTH = 300
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private const val MODEL_INPUT_HEIGHT = 300
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@@ -47,12 +52,7 @@ object FoodModule {
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suspend fun init(context: Context) {
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withContext(Dispatchers.IO) {
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module_mobile = Module.load(copyAssetToCache(context, "best_embedding_model_mobile.pt"))
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ObjectBox.safeDbOp {
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val box = ObjectBox.getBox<Food>()
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if (box?.all?.isEmpty() == true) {
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initDefFoodData(context)
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}
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}
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initDefFoodData(context)
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}
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}
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@@ -65,13 +65,13 @@ object FoodModule {
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// }
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fun bitmap2FloatArray(originBitmap: Bitmap, isRecycle: Boolean): FloatArray? {
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var rgb565Bitmap: Bitmap?=null
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var rgb565Bitmap: Bitmap? = null
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try {
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val scaledBitmap = originBitmap.scale(MODEL_INPUT_WIDTH, MODEL_INPUT_HEIGHT)
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if (isRecycle) {
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originBitmap.recycle()
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}
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rgb565Bitmap = scaledBitmap.copy(Bitmap.Config.RGB_565, false)
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rgb565Bitmap = scaledBitmap.copy(Bitmap.Config.RGB_565, false)
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scaledBitmap.recycle()
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val inputTensor = TensorImageUtils.bitmapToFloat32Tensor(
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rgb565Bitmap,
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@@ -114,7 +114,10 @@ object FoodModule {
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// return queryFoodNameScore(floatArray, queryCount)
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// }
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suspend fun queryFoodNameScore(floatArray: FloatArray?, queryCount: Int = 15): List<IdNameScore> {
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suspend fun queryFoodNameScore(
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floatArray: FloatArray?,
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queryCount: Int = 15
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): List<IdNameScore> {
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if (floatArray == null) return emptyList()
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// val query: Query<Food> = box.query(Food_.foodVector.nearestNeighbors(floatArray, queryCount)).build()
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// //查询比较分数
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@@ -126,15 +129,18 @@ object FoodModule {
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// // 先关闭Query,释放Cursor
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// query.close()
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// }
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Timber.tag("FoodModule").d("queryFood向量:${floatArray.slice(0 until 50).toJsonString()}")
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val idScoreList = ObjectBox.query(floatArray, queryCount)
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val nameScoreList = mutableListOf<IdNameScore>()
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idScoreList.forEach {
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val name = ObjectBox.get(it.id)?.name?:""
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val name = ObjectBox.get(it.id)?.name ?: ""
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nameScoreList.add(IdNameScore(id = it.id, name = name, score = it.score))
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}
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Timber.tag("FoodModule").d("queryFood数据:${nameScoreList.toJsonString()}")
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return nameScoreList
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}
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suspend fun getFoodScoreList(bitmap: Bitmap, queryCount: Int = 15): List<IdNameScore> {
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val floatArray = bitmap2FloatArray(bitmap, false) ?: return emptyList()
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Timber.tag("FoodModule").d("向量:${floatArray.toJsonString()}")
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@@ -165,6 +171,7 @@ object FoodModule {
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Timber.tag("FoodModule").d("getFoodScoreList数据:${sortedScoreList.toJsonString()}")
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return sortedScoreList
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}
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suspend fun queryFood(floatArray: FloatArray, queryCount: Int = 15): List<String> {
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val map = mutableMapOf<String, Int>()
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val nameScoreList = queryFoodNameScore(floatArray, queryCount)
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@@ -177,39 +184,51 @@ object FoodModule {
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}
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data class IdNameScore(
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val id:Long,
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var name:String,
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val id: Long,
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var name: String,
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val score: Double
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)
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suspend fun initDefFoodData(context: Context, action:()-> Unit={}) {
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val count = ObjectBox.getBox<Food>()?.all?.count { it.foodIdx == DEFAULT_FOOD_INDEX }?:0
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if (count > 0) {
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return
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}
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val embeddingsJson = AssetsTool.readAssetsFile(context, "data/embeddings.json")
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val labelsJson = AssetsTool.readAssetsFile(context, "data/labels.json")
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val classInfoJson = AssetsTool.readAssetsFile(context, "data/class_info.json")
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suspend fun initDefFoodData(context: Context, action: () -> Unit = {}) {
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try {
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val count =
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ObjectBox.getBox<Food>()?.all?.count { it.foodIdx == DEFAULT_FOOD_INDEX } ?: 0
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if (count > 0) {
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return
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}
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val embeddingsJson = AssetsTool.readAssetsFile(context, "data/embeddings.json")
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val labelsJson = AssetsTool.readAssetsFile(context, "data/labels.json")
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val classInfoJson = AssetsTool.readAssetsFile(context, "data/class_info.json")
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embeddingsList =
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Gson().fromJson(embeddingsJson, object : TypeToken<List<List<Float>>>() {}.type)
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labelsList = Gson().fromJson(labelsJson, IntArray::class.java)
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classInfo =
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Gson().fromJson(classInfoJson, FoodClassInfo::class.java)
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embeddingsList =
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Gson().fromJson(embeddingsJson, object : TypeToken<List<List<Float>>>() {}.type)
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labelsList = Gson().fromJson(labelsJson, IntArray::class.java)
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classInfo =
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Gson().fromJson(classInfoJson, FoodClassInfo::class.java)
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val foodMap = classInfo.idx_to_class
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val list = mutableListOf<Food>()
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embeddingsList.forEachIndexed { index, floatList ->
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val classIdx = labelsList[index]
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val foodName = foodMap["$classIdx"]
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val array = floatList.toFloatArray()
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// ObjectBox.boxStore.runInTx {
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// box.put(Food(name = foodName, foodVector = array, foodIdx = DEFAULT_FOOD_INDEX))
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// }
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list.add(Food(name = foodName, foodVector = array, foodIdx = DEFAULT_FOOD_INDEX))
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val foodMap = classInfo.idx_to_class
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val list = mutableListOf<Food>()
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val size = embeddingsList.size
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val size2 = labelsList.size
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val size3 = foodMap.size
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Log.d("TAG", "initDefFoodData: $size,$size2,$size3")
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embeddingsList.forEachIndexed { index, floatList ->
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val classIdx = labelsList[index]
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val foodName = foodMap["$classIdx"]
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val array = floatList.toFloatArray()
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// ObjectBox.boxStore.runInTx {
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// box.put(Food(name = foodName, foodVector = array, foodIdx = DEFAULT_FOOD_INDEX))
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// }
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val food = Food(name = foodName, foodVector = array, foodIdx = DEFAULT_FOOD_INDEX)
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list.add(food)
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}
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// val tempList = list.chunked(10)
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ObjectBox.putAll(list)
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action()
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} catch (e: Exception) {
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e.printStackTrace()
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Log.d("TAG", "initDefFoodData: ---${e.message}--")
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}
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ObjectBox.putAll(list)
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action()
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}
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@@ -140,6 +140,7 @@ object ObjectBox {
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dbMutex.withLock { operation() }
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} catch (e: FileCorruptException) {
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// 操作中触发损坏,尝试重建数据库
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e.printStackTrace()
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//val context = boxStore.context
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//deleteDbFiles(context)
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init(MyApp.instance!!)
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@@ -173,19 +174,20 @@ object ObjectBox {
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}
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suspend fun putAll(entities: List<Food>) = safeDbOp {
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getBox<Food>()?.put(entities)
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val box = getBox<Food>()
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box?.put(entities)
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}
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suspend fun filter(name:String?) = safeDbOp {
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suspend fun filter(name: String?) = safeDbOp {
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val list = getBox<Food>()?.all?.distinctBy { it.name }
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if (name.isNullOrBlank().not()) {
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list?.filter { it.name?.contains(name) == true }
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} else {
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list
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}?:emptyList()
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} ?: emptyList()
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}
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suspend fun remove(name:String) = safeDbOp {
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suspend fun remove(name: String) = safeDbOp {
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getBox<Food>()?.run {
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val filterIdList = all.filter { it.name == name }.map { it.id }
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removeByIds(filterIdList)
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