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[AI] Add Hybrid Image Pattern Finder sample #2854
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213 changes: 213 additions & 0 deletions
213
...main/java/com/google/firebase/quickstart/ai/feature/hybrid/HybridImagePatternViewModel.kt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,213 @@ | ||
| package com.google.firebase.quickstart.ai.feature.hybrid | ||
|
|
||
| import android.content.ContentResolver | ||
| import android.graphics.Bitmap | ||
| import android.graphics.BitmapFactory | ||
| import android.net.Uri | ||
| import androidx.lifecycle.ViewModel | ||
| import androidx.lifecycle.viewModelScope | ||
| import com.google.firebase.Firebase | ||
| import com.google.firebase.ai.DownloadStatus | ||
| import com.google.firebase.ai.InferenceMode | ||
| import com.google.firebase.ai.InferenceSource | ||
| import com.google.firebase.ai.OnDeviceConfig | ||
| import com.google.firebase.ai.OnDeviceModelStatus | ||
| import com.google.firebase.ai.ai | ||
| import com.google.firebase.ai.type.GenerativeBackend | ||
| import com.google.firebase.ai.type.PublicPreviewAPI | ||
| import com.google.firebase.ai.type.content | ||
| import com.google.firebase.quickstart.ai.ui.HybridImagePatternUiState | ||
| import kotlinx.coroutines.Dispatchers | ||
| import kotlinx.coroutines.flow.MutableStateFlow | ||
| import kotlinx.coroutines.flow.StateFlow | ||
| import kotlinx.coroutines.flow.update | ||
| import kotlinx.coroutines.launch | ||
| import kotlinx.coroutines.withContext | ||
| import kotlinx.serialization.Serializable | ||
|
|
||
| @Serializable | ||
| object HybridImagePatternRoute | ||
|
|
||
| @OptIn(PublicPreviewAPI::class) | ||
| class HybridImagePatternViewModel : ViewModel() { | ||
| val uiState: StateFlow<HybridImagePatternUiState> | ||
| field = MutableStateFlow(HybridImagePatternUiState()) | ||
|
|
||
| // Used only to check the on-device model status and trigger its download. | ||
| private val statusCheckModel = Firebase.ai( | ||
| backend = GenerativeBackend.googleAI(), | ||
| useLimitedUseAppCheckTokens = true | ||
| ).generativeModel( | ||
| modelName = MODEL_NAME, | ||
| onDeviceConfig = OnDeviceConfig(mode = InferenceMode.PREFER_ON_DEVICE) | ||
| ) | ||
|
|
||
| init { | ||
| checkAndDownloadModel() | ||
| } | ||
|
|
||
| private fun checkAndDownloadModel() { | ||
| viewModelScope.launch { | ||
| try { | ||
| val status = statusCheckModel.onDeviceExtension?.checkStatus() | ||
| updateStatus(status) | ||
|
|
||
| if (status == OnDeviceModelStatus.DOWNLOADABLE) { | ||
| statusCheckModel.onDeviceExtension?.download()?.collect { downloadStatus -> | ||
| when (downloadStatus) { | ||
| is DownloadStatus.DownloadStarted -> { | ||
| uiState.update { it.copy(modelStatus = "Downloading model...") } | ||
| } | ||
|
|
||
| is DownloadStatus.DownloadInProgress -> { | ||
| val progress = downloadStatus.totalBytesDownloaded | ||
| uiState.update { it.copy(modelStatus = "Downloading: $progress bytes downloaded") } | ||
| } | ||
|
|
||
| is DownloadStatus.DownloadCompleted -> { | ||
| uiState.update { it.copy(modelStatus = "Model ready") } | ||
| } | ||
|
|
||
| is DownloadStatus.DownloadFailed -> { | ||
| uiState.update { | ||
| it.copy( | ||
| modelStatus = "Download failed", | ||
| errorMessage = "Model download failed" | ||
| ) | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } catch (e: Exception) { | ||
| uiState.update { it.copy(modelStatus = "Error checking status", errorMessage = e.message) } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| private fun updateStatus(status: OnDeviceModelStatus?) { | ||
| val statusText = when (status) { | ||
| OnDeviceModelStatus.AVAILABLE -> "Model available" | ||
| OnDeviceModelStatus.DOWNLOADABLE -> "Model downloadable" | ||
| OnDeviceModelStatus.DOWNLOADING -> "Model downloading..." | ||
| else -> "On-device model unavailable" | ||
| } | ||
| uiState.update { it.copy(modelStatus = statusText) } | ||
| } | ||
|
|
||
| fun setInferenceMode(mode: InferenceModeOption) { | ||
| uiState.update { it.copy(selectedMode = mode) } | ||
| } | ||
|
|
||
| fun setFirstImage(bitmap: Bitmap) { | ||
| uiState.update { it.copy(firstImage = bitmap, errorMessage = null) } | ||
| } | ||
|
|
||
| fun setSecondImage(bitmap: Bitmap) { | ||
| uiState.update { it.copy(secondImage = bitmap, errorMessage = null) } | ||
| } | ||
|
|
||
| /** | ||
| * Decodes the image at [uri] off the main thread, downsampling it so that its longest | ||
| * edge is at most [MAX_IMAGE_DIMENSION] pixels, and stores it in the given [slot] (1 or 2). | ||
| */ | ||
| fun loadImageFromUri(resolver: ContentResolver, uri: Uri, slot: Int) { | ||
| viewModelScope.launch { | ||
| try { | ||
| val bitmap = withContext(Dispatchers.IO) { decodeDownsampled(resolver, uri) } | ||
| if (bitmap == null) { | ||
| uiState.update { it.copy(errorMessage = "Could not decode the selected image") } | ||
| } else if (slot == 1) { | ||
| setFirstImage(bitmap) | ||
| } else { | ||
| setSecondImage(bitmap) | ||
| } | ||
| } catch (e: Exception) { | ||
| uiState.update { it.copy(errorMessage = "Error loading image: ${e.message}") } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| private fun decodeDownsampled(resolver: ContentResolver, uri: Uri): Bitmap? { | ||
| // First pass: read only the bounds to compute a sample size. | ||
| val bounds = BitmapFactory.Options().apply { inJustDecodeBounds = true } | ||
| resolver.openInputStream(uri)?.use { BitmapFactory.decodeStream(it, null, bounds) } | ||
| if (bounds.outWidth <= 0 || bounds.outHeight <= 0) return null | ||
|
|
||
| var sampleSize = 1 | ||
| while (maxOf(bounds.outWidth, bounds.outHeight) / sampleSize > MAX_IMAGE_DIMENSION) { | ||
| sampleSize *= 2 | ||
| } | ||
|
|
||
| // Second pass: decode the downsampled bitmap. | ||
| val options = BitmapFactory.Options().apply { inSampleSize = sampleSize } | ||
| return resolver.openInputStream(uri)?.use { BitmapFactory.decodeStream(it, null, options) } | ||
| } | ||
|
|
||
| fun findCommonPatterns() { | ||
| val firstBitmap = uiState.value.firstImage | ||
| val secondBitmap = uiState.value.secondImage | ||
| if (firstBitmap == null || secondBitmap == null) { | ||
| uiState.update { it.copy(errorMessage = "Please provide both images first.") } | ||
| return | ||
| } | ||
| val mode = uiState.value.selectedMode.mode | ||
|
|
||
| viewModelScope.launch { | ||
| uiState.update { | ||
| it.copy( | ||
| isAnalyzing = true, | ||
| errorMessage = null, | ||
| resultText = null, | ||
| inferenceMode = "" | ||
| ) | ||
| } | ||
| try { | ||
| val model = Firebase.ai( | ||
| backend = GenerativeBackend.googleAI(), | ||
| useLimitedUseAppCheckTokens = true | ||
| ).generativeModel( | ||
| modelName = MODEL_NAME, | ||
| onDeviceConfig = OnDeviceConfig(mode = mode) | ||
| ) | ||
|
|
||
| val prompt = content { | ||
| image(firstBitmap) | ||
| image(secondBitmap) | ||
| text( | ||
| """ | ||
| Compare these two images and find common patterns, themes, objects, or visual elements shared between both images. | ||
| """.trimIndent() | ||
| ) | ||
| } | ||
|
|
||
| val response = model.generateContent(prompt) | ||
| val text = response.text | ||
| val inferenceMode = if (response.inferenceSource == InferenceSource.ON_DEVICE) { | ||
| "On-device" | ||
| } else { | ||
| "Cloud" | ||
| } | ||
| if (text != null) { | ||
| uiState.update { | ||
| it.copy( | ||
| resultText = text, | ||
| inferenceMode = inferenceMode | ||
| ) | ||
| } | ||
| } else { | ||
| uiState.update { it.copy(errorMessage = "Could not find patterns from the provided images") } | ||
| } | ||
| } catch (e: Exception) { | ||
| uiState.update { it.copy(errorMessage = "Error (${mode}): ${e.message}") } | ||
| } finally { | ||
| uiState.update { it.copy(isAnalyzing = false) } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| companion object { | ||
| private const val MODEL_NAME = "gemini-3.5-flash-lite" | ||
| private const val MAX_IMAGE_DIMENSION = 1024 | ||
| } | ||
| } | ||
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