feat: [detection] update ui & change newest model

app/src/main/java/com/example/palmguardapp/data/repository/DiseaseRepository.kt

@@ -4,45 +4,6 @@ import com.example.palmguardapp.data.local.entity.DiseaseDiagnose
 import com.example.palmguardapp.data.local.room.DiseaseDiagnoseDao
 import kotlinx.coroutines.flow.Flow
 
-//class DiseaseRepository private constructor(
-//    private val apiService: ApiService
-//) {
-//
-//    suspend fun getDiseaseById(id: String): Flow<Result<DiseaseByIdResponse>> = flow {
-//        emit(Result.Loading)
-//        val response = apiService.getDiseaseById(id)
-//        emit(Result.Success(response))
-//    }.catch { e ->
-//        emit(Result.Error(e.message.toString()))
-//    }
-//
-//    suspend fun getAllDiseaseDetail(): Flow<Result<DiseaseDetailResponse>> = flow {
-//        emit(Result.Loading)
-//        val response = apiService.getAllDiseaseDetail()
-//        emit(Result.Success(response))
-//    }.catch { e ->
-//        emit(Result.Error(e.message.toString()))
-//    }
-//
-//    suspend fun getDiseaseDetailById(id: String): Flow<Result<DiseaseDetailByIdResponse>> = flow {
-//        emit(Result.Loading)
-//        val response = apiService.getDiseaseDetailById(id)
-//        emit(Result.Success(response))
-//    }.catch { e ->
-//        emit(Result.Error(e.message.toString()))
-//    }
-//
-//    companion object {
-//        @Volatile
-//        private var instance: DiseaseRepository? = null
-//
-//        fun getInstance(apiService: ApiService): DiseaseRepository =
-//            instance ?: synchronized(this) {
-//                instance ?: DiseaseRepository(apiService).also { instance = it }
-//            }
-//    }
-//}
-
 class DiseaseRepository private constructor(
     private val diseaseDiagnoseDao: DiseaseDiagnoseDao
 ) {

app/src/main/java/com/example/palmguardapp/foundation/classification/ImageClassifier.kt

@@ -1,3 +1,4 @@
+// Import library yang dibutuhkan untuk context, bitmap, logging, dan TensorFlow Lite
 import android.content.Context
 import android.graphics.Bitmap
 import android.util.Log
@@ -9,51 +10,69 @@ import org.tensorflow.lite.support.image.TensorImage
 import org.tensorflow.lite.support.image.ops.ResizeOp
 import org.tensorflow.lite.support.tensorbuffer.TensorBuffer
 
-
+// Kelas utama untuk klasifikasi gambar menggunakan model ML TFLite
 class ImageClassifier(private val context: Context) {
 
+    // Ukuran input gambar yang dibutuhkan model
     private val imageSize = 224
+
+    // Daftar label kelas dari model
     private val classes = arrayOf("Brown Spots", "Healthy", "Unknown")
 
+    // ImageProcessor untuk mengubah ukuran dan menormalisasi gambar agar sesuai dengan input model
     private val imageProcessor = ImageProcessor.Builder()
-        .add(ResizeOp(imageSize, imageSize, ResizeOp.ResizeMethod.BILINEAR))
+        .add(ResizeOp(imageSize, imageSize, ResizeOp.ResizeMethod.BILINEAR)) // Resize gambar ke 224x224
-        .add(NormalizeOp(0f, 255f))
+        .add(NormalizeOp(0f, 255f)) // Normalisasi piksel gambar ke range 0–1
         .build()
 
+    // Fungsi utama untuk mengklasifikasikan gambar
     fun classifyImage(image: Bitmap): Pair<String, Float>? {
+        // Membuat instance model
         val model = Model.newInstance(context)
 
+        // Mengonversi gambar bitmap ke TensorImage dengan tipe data FLOAT32
         val tensorImage = TensorImage(DataType.FLOAT32)
-        val convertedBitmap = image.copy(Bitmap.Config.ARGB_8888, true)
+        val convertedBitmap = image.copy(Bitmap.Config.ARGB_8888, true) // Salin bitmap agar bisa diolah
         tensorImage.load(convertedBitmap)
+
+        // Proses preprocessing gambar: resize + normalisasi
         val processedImage = imageProcessor.process(tensorImage)
 
+        // Menyiapkan buffer input model dengan shape dan tipe data yang sesuai
         val inputFeature0 = TensorBuffer.createFixedSize(intArrayOf(1, imageSize, imageSize, 3), DataType.FLOAT32)
         inputFeature0.loadBuffer(processedImage.buffer)
 
+        // Memproses input melalui model dan mendapatkan output
         val outputs = model.process(inputFeature0)
         val outputFeature0 = outputs.outputFeature0AsTensorBuffer
 
+        // Mengambil array probabilitas prediksi dari hasil output
         val confidences = outputFeature0.floatArray
         Log.d("ImageClassifier", "Confidence: ${confidences.size}")
+
+        // Logging setiap confidence untuk tiap kelas
         for (i in confidences.indices) {
             Log.d("ImageClassifier", "Class $i (${classes[i]}): ${confidences[i]}")
         }
 
+        // Mencari indeks prediksi dengan confidence tertinggi
         val maxPos = confidences.indices.maxByOrNull { confidences[it] } ?: -1
-        val maxConfidence =  (maxOf(confidences[maxPos]) * 100).toFloat()
+        val maxConfidence = (maxOf(confidences[maxPos]) * 100).toFloat() // Konversi ke persen
         Log.d("ImageClassifier", "Max Position: $maxPos, Max Confidence: $maxConfidence")
 
+        // Menutup instance model untuk membebaskan resource
         model.close()
 
+        // Mengembalikan hasil klasifikasi jika confidence mencukupi dan bukan kelas Unknown
         return if (maxPos >= 0 && maxConfidence > THRESHOLD_CONFIDENCE && classes[maxPos] != "Unknown") {
             Pair(classes[maxPos], maxConfidence)
         } else {
-            null
+            null // Tidak ada hasil yang cukup meyakinkan
         }
     }
 
     companion object {
+        // Batas minimum confidence yang dianggap valid (dalam persen)
         private const val THRESHOLD_CONFIDENCE = 0.5f
     }
-}
+}

app/src/main/java/com/example/palmguardapp/ui/detection/DetectionViewModel.kt

@@ -29,7 +29,6 @@ class DetectionViewModel(private val historyDiagnoseRepository: HistoryDiagnoseR
     fun deleteHistory(historyDiagnose: HistoryDiagnose) {
         viewModelScope.launch {
             historyDiagnoseRepository.delete(historyDiagnose)
-            // Refresh the list after deletion
             getDetectionList()
         }
     }

app/src/main/java/com/example/palmguardapp/ui/home/HomeFragment.kt

@@ -49,12 +49,6 @@ class HomeFragment : Fragment(R.layout.fragment_home) {
     private val diseaseToId = mapOf(
         "Brown Spots" to "D-001",
         "Healthy" to "D-002",
-//        "Bird Eye Spot" to "D-003",
-//        "Brown Blight" to "D-004",
-//        "Gray Light" to "D-005",
-//        "Red Leaf Spot" to "D-006",
-//        "White Spot" to "D-007",
-//        "Healthy" to "D-008"
     )
 
     private lateinit var cameraLauncher: ActivityResultLauncher<Intent>
@@ -219,38 +213,6 @@ class HomeFragment : Fragment(R.layout.fragment_home) {
         Log.d("saveImageAndFetchData", "Date: $date")
         val dateNow = formatter.format(date)
         val diseaseId = diseaseToId[diagnosis]
-//        diseaseId?.let { id ->
-//            viewModel.getDiseaseById(id)
-//            viewModel.dataDisease.collect { result ->
-//                when (result) {
-//                    is Result.Success -> {
-//                        val diseaseData = result.data
-//                        Log.d("HomeFragment", "Disease Data: $diseaseData")
-//                        val historyDiagnose = HistoryDiagnose(
-//                            name = diagnosis,
-//                            imageUri = imageUri.toString(),
-//                            diagnosis = diseaseData.data?.diseaseExplanation ?: "",
-//                            recommendation = diseaseData.data?.diseaseRecommendation ?: "",
-//                            confidence = confidence.toString(),
-//                            date = dateNow
-//                        )
-//
-//                        viewModel.saveDiagnose(historyDiagnose)
-//                        lastDiagnosis = historyDiagnose
-//                        Log.d("HomeFragment", "History Diagnose: $historyDiagnose")
-//                        binding.progressResult.visibility = View.GONE
-//                        restartFragment()
-//                        navigateToDiagnoseDetail(historyDiagnose)
-//                    }
-//                    is Result.Error -> {
-//                        // Handle error state
-//                    }
-//                    Result.Loading -> {
-//                        binding.progressResult.visibility = View.VISIBLE
-//                    }
-//                }
-//            }
-//        }
         diseaseId?.let { id ->
             viewModel.getDiseaseById(id)
 
@@ -317,7 +279,6 @@ class HomeFragment : Fragment(R.layout.fragment_home) {
         binding.tvHsHistoryEmpty.visibility = View.GONE
     }
 
-
     override fun onDestroyView() {
         super.onDestroyView()
         _binding = null

app/src/main/java/com/example/palmguardapp/ui/listDisease/DiseaseViewModel.kt

@@ -18,15 +18,6 @@ class DiseaseViewModel(private val diseaseRepository: DiseaseRepository) : ViewM
     private val _diseaseById = MutableSharedFlow<Result<DiseaseDiagnose?>>()
     val diseaseById: Flow<Result<DiseaseDiagnose?>> = _diseaseById.asSharedFlow()
 
-//    fun getAllDisease() {
-//        viewModelScope.launch {
-//            _listDisease.emit(Result.Loading)
-//            diseaseRepository.getAllDisease().collect { diseases ->
-//                _listDisease.emit(Result.Success(diseases))
-//            }
-//        }
-//    }
-
     fun getDiseaseById(id: String) {
         viewModelScope.launch {
             _diseaseById.emit(Result.Loading)

app/src/main/res/layout/fragment_home.xml

@@ -124,7 +124,7 @@
                         android:id="@+id/tv_hs_phone_analyze"
                         android:layout_width="wrap_content"
                         android:layout_height="wrap_content"
-                        android:text="Ambil Gambar"
+                        android:text="Analisis Hasil"
                         android:textColor="@color/greenGeneral"
                         android:textSize="14sp"
                         android:textStyle="bold"

app/src/main/res/menu/bottom_nav.xml

@@ -7,5 +7,5 @@
     <item
         android:id="@+id/detection"
         android:icon="@drawable/hs_trace_black_img"
-        android:title="Deteksi" />
+        android:title="Riwayat" />
 </menu>