feat: android periodic work manager task

* fix: exif gps parsing of malformed data

* chore: e2e test

.github/workflows/build-mobile.yml

@@ -20,6 +20,30 @@ on:
         required: true
       ANDROID_STORE_PASSWORD:
         required: true
+      APP_STORE_CONNECT_API_KEY_ID:
+        required: true
+      APP_STORE_CONNECT_API_KEY_ISSUER_ID:
+        required: true
+      APP_STORE_CONNECT_API_KEY:
+        required: true
+      IOS_CERTIFICATE_P12:
+        required: true
+      IOS_CERTIFICATE_PASSWORD:
+        required: true
+      IOS_PROVISIONING_PROFILE:
+        required: true
+      IOS_PROVISIONING_PROFILE_SHARE_EXTENSION:
+        required: true
+      IOS_PROVISIONING_PROFILE_WIDGET_EXTENSION:
+        required: true
+      IOS_DEVELOPMENT_PROVISIONING_PROFILE:
+        required: true
+      IOS_DEVELOPMENT_PROVISIONING_PROFILE_SHARE_EXTENSION:
+        required: true
+      IOS_DEVELOPMENT_PROVISIONING_PROFILE_WIDGET_EXTENSION:
+        required: true
+      FASTLANE_TEAM_ID:
+        required: true
   pull_request:
   push:
     branches: [main]

.github/workflows/prepare-release.yml

@@ -99,6 +99,20 @@ jobs:
       ALIAS: ${{ secrets.ALIAS }}
       ANDROID_KEY_PASSWORD: ${{ secrets.ANDROID_KEY_PASSWORD }}
       ANDROID_STORE_PASSWORD: ${{ secrets.ANDROID_STORE_PASSWORD }}
+      # iOS secrets
+      APP_STORE_CONNECT_API_KEY_ID: ${{ secrets.APP_STORE_CONNECT_API_KEY_ID }}
+      APP_STORE_CONNECT_API_KEY_ISSUER_ID: ${{ secrets.APP_STORE_CONNECT_API_KEY_ISSUER_ID }}
+      APP_STORE_CONNECT_API_KEY: ${{ secrets.APP_STORE_CONNECT_API_KEY }}
+      IOS_CERTIFICATE_P12: ${{ secrets.IOS_CERTIFICATE_P12 }}
+      IOS_CERTIFICATE_PASSWORD: ${{ secrets.IOS_CERTIFICATE_PASSWORD }}
+      IOS_PROVISIONING_PROFILE: ${{ secrets.IOS_PROVISIONING_PROFILE }}
+      IOS_PROVISIONING_PROFILE_SHARE_EXTENSION: ${{ secrets.IOS_PROVISIONING_PROFILE_SHARE_EXTENSION }}
+      IOS_PROVISIONING_PROFILE_WIDGET_EXTENSION: ${{ secrets.IOS_PROVISIONING_PROFILE_WIDGET_EXTENSION }}
+      IOS_DEVELOPMENT_PROVISIONING_PROFILE: ${{ secrets.IOS_DEVELOPMENT_PROVISIONING_PROFILE }}
+      IOS_DEVELOPMENT_PROVISIONING_PROFILE_SHARE_EXTENSION: ${{ secrets.IOS_DEVELOPMENT_PROVISIONING_PROFILE_SHARE_EXTENSION }}
+      IOS_DEVELOPMENT_PROVISIONING_PROFILE_WIDGET_EXTENSION: ${{ secrets.IOS_DEVELOPMENT_PROVISIONING_PROFILE_WIDGET_EXTENSION }}
+      FASTLANE_TEAM_ID: ${{ secrets.FASTLANE_TEAM_ID }}
+
     with:
       ref: ${{ needs.bump_version.outputs.ref }}
       environment: production

cli/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@immich/cli",
-  "version": "2.2.99",
+  "version": "2.2.100",
   "description": "Command Line Interface (CLI) for Immich",
   "type": "module",
   "exports": "./dist/index.js",

docs/static/archived-versions.json

@@ -1,4 +1,8 @@
 [
+  {
+    "label": "v2.2.2",
+    "url": "https://docs.v2.2.2.archive.immich.app"
+  },
   {
     "label": "v2.2.1",
     "url": "https://docs.v2.2.1.archive.immich.app"

e2e/package.json

@@ -1,6 +1,6 @@
 {
   "name": "immich-e2e",
-  "version": "2.2.1",
+  "version": "2.2.2",
   "description": "",
   "main": "index.js",
   "type": "module",

e2e/src/api/specs/asset.e2e-spec.ts

@@ -1140,6 +1140,16 @@ describe('/asset', () => {
           },
         },
       },
+      {
+        input: 'metadata/gps-position/empty_gps.jpg',
+        expected: {
+          type: AssetTypeEnum.Image,
+          exifInfo: {
+            latitude: null,
+            longitude: null,
+          },
+        },
+      },
     ];
 
     it.each(tests)(`should upload and generate a thumbnail for different file types`, async ({ input, expected }) => {

machine-learning/immich_ml/models/ocr/detection.py

@@ -1,8 +1,10 @@
 from typing import Any
 
+import cv2
 import numpy as np
+from numpy.typing import NDArray
 from PIL import Image
-from rapidocr.ch_ppocr_det import TextDetector as RapidTextDetector
+from rapidocr.ch_ppocr_det.utils import DBPostProcess
 from rapidocr.inference_engine.base import FileInfo, InferSession
 from rapidocr.utils import DownloadFile, DownloadFileInput
 from rapidocr.utils.typings import EngineType, LangDet, OCRVersion, TaskType
@@ -10,11 +12,10 @@ from rapidocr.utils.typings import ModelType as RapidModelType
 
 from immich_ml.config import log
 from immich_ml.models.base import InferenceModel
-from immich_ml.models.transforms import decode_cv2
 from immich_ml.schemas import ModelFormat, ModelSession, ModelTask, ModelType
 from immich_ml.sessions.ort import OrtSession
 
-from .schemas import OcrOptions, TextDetectionOutput
+from .schemas import TextDetectionOutput
 
 
 class TextDetector(InferenceModel):
@@ -24,13 +25,20 @@ class TextDetector(InferenceModel):
     def __init__(self, model_name: str, **model_kwargs: Any) -> None:
         super().__init__(model_name, **model_kwargs, model_format=ModelFormat.ONNX)
         self.max_resolution = 736
-        self.min_score = 0.5
-        self.score_mode = "fast"
+        self.mean = np.array([0.5, 0.5, 0.5], dtype=np.float32)
+        self.std_inv = np.float32(1.0) / (np.array([0.5, 0.5, 0.5], dtype=np.float32) * 255.0)
         self._empty: TextDetectionOutput = {
-            "image": np.empty(0, dtype=np.float32),
             "boxes": np.empty(0, dtype=np.float32),
             "scores": np.empty(0, dtype=np.float32),
         }
+        self.postprocess = DBPostProcess(
+            thresh=0.3,
+            box_thresh=model_kwargs.get("minScore", 0.5),
+            max_candidates=1000,
+            unclip_ratio=1.6,
+            use_dilation=True,
+            score_mode="fast",
+        )
 
     def _download(self) -> None:
         model_info = InferSession.get_model_url(
@@ -52,35 +60,65 @@ class TextDetector(InferenceModel):
 
     def _load(self) -> ModelSession:
         # TODO: support other runtime sessions
-        session = OrtSession(self.model_path)
-        self.model = RapidTextDetector(
-            OcrOptions(
-                session=session.session,
-                limit_side_len=self.max_resolution,
-                limit_type="min",
-                box_thresh=self.min_score,
-                score_mode=self.score_mode,
-            )
-        )
-        return session
+        return OrtSession(self.model_path)
 
-    def _predict(self, inputs: bytes | Image.Image) -> TextDetectionOutput:
-        results = self.model(decode_cv2(inputs))
-        if results.boxes is None or results.scores is None or results.img is None:
+    # partly adapted from RapidOCR
+    def _predict(self, inputs: Image.Image) -> TextDetectionOutput:
+        w, h = inputs.size
+        if w < 32 or h < 32:
+            return self._empty
+        out = self.session.run(None, {"x": self._transform(inputs)})[0]
+        boxes, scores = self.postprocess(out, (h, w))
+        if len(boxes) == 0:
             return self._empty
         return {
-            "image": results.img,
-            "boxes": np.array(results.boxes, dtype=np.float32),
-            "scores": np.array(results.scores, dtype=np.float32),
+            "boxes": self.sorted_boxes(boxes),
+            "scores": np.array(scores, dtype=np.float32),
         }
 
+    # adapted from RapidOCR
+    def _transform(self, img: Image.Image) -> NDArray[np.float32]:
+        if img.height < img.width:
+            ratio = float(self.max_resolution) / img.height
+        else:
+            ratio = float(self.max_resolution) / img.width
+
+        resize_h = int(img.height * ratio)
+        resize_w = int(img.width * ratio)
+
+        resize_h = int(round(resize_h / 32) * 32)
+        resize_w = int(round(resize_w / 32) * 32)
+        resized_img = img.resize((int(resize_w), int(resize_h)), resample=Image.Resampling.LANCZOS)
+
+        img_np: NDArray[np.float32] = cv2.cvtColor(np.array(resized_img, dtype=np.float32), cv2.COLOR_RGB2BGR)  # type: ignore
+        img_np -= self.mean
+        img_np *= self.std_inv
+        img_np = np.transpose(img_np, (2, 0, 1))
+        return np.expand_dims(img_np, axis=0)
+
+    def sorted_boxes(self, dt_boxes: NDArray[np.float32]) -> NDArray[np.float32]:
+        if len(dt_boxes) == 0:
+            return dt_boxes
+
+        # Sort by y, then identify lines, then sort by (line, x)
+        y_order = np.argsort(dt_boxes[:, 0, 1], kind="stable")
+        sorted_y = dt_boxes[y_order, 0, 1]
+
+        line_ids = np.empty(len(dt_boxes), dtype=np.int32)
+        line_ids[0] = 0
+        np.cumsum(np.abs(np.diff(sorted_y)) >= 10, out=line_ids[1:])
+
+        # Create composite sort key for final ordering
+        # Shift line_ids by large factor, add x for tie-breaking
+        sort_key = line_ids[y_order] * 1e6 + dt_boxes[y_order, 0, 0]
+        final_order = np.argsort(sort_key, kind="stable")
+        sorted_boxes: NDArray[np.float32] = dt_boxes[y_order[final_order]]
+        return sorted_boxes
+
     def configure(self, **kwargs: Any) -> None:
         if (max_resolution := kwargs.get("maxResolution")) is not None:
             self.max_resolution = max_resolution
-            self.model.limit_side_len = max_resolution
         if (min_score := kwargs.get("minScore")) is not None:
-            self.min_score = min_score
-            self.model.postprocess_op.box_thresh = min_score
+            self.postprocess.box_thresh = min_score
         if (score_mode := kwargs.get("scoreMode")) is not None:
-            self.score_mode = score_mode
-            self.model.postprocess_op.score_mode = score_mode
+            self.postprocess.score_mode = score_mode

machine-learning/immich_ml/models/ocr/recognition.py

@@ -1,9 +1,8 @@
 from typing import Any
 
-import cv2
 import numpy as np
 from numpy.typing import NDArray
-from PIL.Image import Image
+from PIL import Image
 from rapidocr.ch_ppocr_rec import TextRecInput
 from rapidocr.ch_ppocr_rec import TextRecognizer as RapidTextRecognizer
 from rapidocr.inference_engine.base import FileInfo, InferSession
@@ -14,6 +13,7 @@ from rapidocr.utils.vis_res import VisRes
 
 from immich_ml.config import log, settings
 from immich_ml.models.base import InferenceModel
+from immich_ml.models.transforms import pil_to_cv2
 from immich_ml.schemas import ModelFormat, ModelSession, ModelTask, ModelType
 from immich_ml.sessions.ort import OrtSession
 
@@ -65,17 +65,16 @@ class TextRecognizer(InferenceModel):
         )
         return session
 
-    def _predict(self, _: Image, texts: TextDetectionOutput) -> TextRecognitionOutput:
-        boxes, img, box_scores = texts["boxes"], texts["image"], texts["scores"]
+    def _predict(self, img: Image.Image, texts: TextDetectionOutput) -> TextRecognitionOutput:
+        boxes, box_scores = texts["boxes"], texts["scores"]
         if boxes.shape[0] == 0:
             return self._empty
         rec = self.model(TextRecInput(img=self.get_crop_img_list(img, boxes)))
         if rec.txts is None:
             return self._empty
 
-        height, width = img.shape[0:2]
-        boxes[:, :, 0] /= width
-        boxes[:, :, 1] /= height
+        boxes[:, :, 0] /= img.width
+        boxes[:, :, 1] /= img.height
 
         text_scores = np.array(rec.scores)
         valid_text_score_idx = text_scores > self.min_score
@@ -87,7 +86,7 @@ class TextRecognizer(InferenceModel):
             "textScore": text_scores[valid_text_score_idx],
         }
 
-    def get_crop_img_list(self, img: NDArray[np.float32], boxes: NDArray[np.float32]) -> list[NDArray[np.float32]]:
+    def get_crop_img_list(self, img: Image.Image, boxes: NDArray[np.float32]) -> list[NDArray[np.uint8]]:
         img_crop_width = np.maximum(
             np.linalg.norm(boxes[:, 1] - boxes[:, 0], axis=1), np.linalg.norm(boxes[:, 2] - boxes[:, 3], axis=1)
         ).astype(np.int32)
@@ -98,22 +97,55 @@ class TextRecognizer(InferenceModel):
         pts_std[:, 1:3, 0] = img_crop_width[:, None]
         pts_std[:, 2:4, 1] = img_crop_height[:, None]
 
-        img_crop_sizes = np.stack([img_crop_width, img_crop_height], axis=1).tolist()
-        imgs: list[NDArray[np.float32]] = []
-        for box, pts_std, dst_size in zip(list(boxes), list(pts_std), img_crop_sizes):
-            M = cv2.getPerspectiveTransform(box, pts_std)
-            dst_img: NDArray[np.float32] = cv2.warpPerspective(
-                img,
-                M,
-                dst_size,
-                borderMode=cv2.BORDER_REPLICATE,
-                flags=cv2.INTER_CUBIC,
-            )  # type: ignore
-            dst_height, dst_width = dst_img.shape[0:2]
+        img_crop_sizes = np.stack([img_crop_width, img_crop_height], axis=1)
+        all_coeffs = self._get_perspective_transform(pts_std, boxes)
+        imgs: list[NDArray[np.uint8]] = []
+        for coeffs, dst_size in zip(all_coeffs, img_crop_sizes):
+            dst_img = img.transform(
+                size=tuple(dst_size),
+                method=Image.Transform.PERSPECTIVE,
+                data=tuple(coeffs),
+                resample=Image.Resampling.BICUBIC,
+            )
+
+            dst_width, dst_height = dst_img.size
             if dst_height * 1.0 / dst_width >= 1.5:
-                dst_img = np.rot90(dst_img)
-            imgs.append(dst_img)
+                dst_img = dst_img.rotate(90, expand=True)
+            imgs.append(pil_to_cv2(dst_img))
+
         return imgs
 
+    def _get_perspective_transform(self, src: NDArray[np.float32], dst: NDArray[np.float32]) -> NDArray[np.float32]:
+        N = src.shape[0]
+        x, y = src[:, :, 0], src[:, :, 1]
+        u, v = dst[:, :, 0], dst[:, :, 1]
+        A = np.zeros((N, 8, 9), dtype=np.float32)
+
+        # Fill even rows (0, 2, 4, 6): [x, y, 1, 0, 0, 0, -u*x, -u*y, -u]
+        A[:, ::2, 0] = x
+        A[:, ::2, 1] = y
+        A[:, ::2, 2] = 1
+        A[:, ::2, 6] = -u * x
+        A[:, ::2, 7] = -u * y
+        A[:, ::2, 8] = -u
+
+        # Fill odd rows (1, 3, 5, 7): [0, 0, 0, x, y, 1, -v*x, -v*y, -v]
+        A[:, 1::2, 3] = x
+        A[:, 1::2, 4] = y
+        A[:, 1::2, 5] = 1
+        A[:, 1::2, 6] = -v * x
+        A[:, 1::2, 7] = -v * y
+        A[:, 1::2, 8] = -v
+
+        # Solve using SVD for all matrices at once
+        _, _, Vt = np.linalg.svd(A)
+        H = Vt[:, -1, :].reshape(N, 3, 3)
+        H = H / H[:, 2:3, 2:3]
+
+        # Extract the 8 coefficients for each transformation
+        return np.column_stack(
+            [H[:, 0, 0], H[:, 0, 1], H[:, 0, 2], H[:, 1, 0], H[:, 1, 1], H[:, 1, 2], H[:, 2, 0], H[:, 2, 1]]
+        )  # pyright: ignore[reportReturnType]
+
     def configure(self, **kwargs: Any) -> None:
         self.min_score = kwargs.get("minScore", self.min_score)

machine-learning/immich_ml/models/ocr/schemas.py

@@ -7,7 +7,6 @@ from typing_extensions import TypedDict
 
 
 class TextDetectionOutput(TypedDict):
-    image: npt.NDArray[np.float32]
     boxes: npt.NDArray[np.float32]
     scores: npt.NDArray[np.float32]
 

machine-learning/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "immich-ml"
-version = "2.2.1"
+version = "2.2.2"
 description = ""
 authors = [{ name = "Hau Tran", email = "alex.tran1502@gmail.com" }]
 requires-python = ">=3.10,<4.0"

mobile/android/app/src/main/kotlin/app/alextran/immich/background/BackgroundEngineLock.kt

@@ -43,8 +43,8 @@ class BackgroundEngineLock(context: Context) : BackgroundWorkerLockApi, ImmichPl
 
   override fun onAttachedToEngine(binding: FlutterPlugin.FlutterPluginBinding) {
     super.onAttachedToEngine(binding)
-    checkAndEnforceBackgroundLock(binding.applicationContext)
     engineCount.incrementAndGet()
+    checkAndEnforceBackgroundLock(binding.applicationContext)
     Log.i(TAG, "Flutter engine attached. Attached Engines count: $engineCount")
   }
 

mobile/android/app/src/main/kotlin/app/alextran/immich/background/BackgroundWorkerApiImpl.kt

@@ -5,8 +5,10 @@ import android.provider.MediaStore
 import android.util.Log
 import androidx.work.BackoffPolicy
 import androidx.work.Constraints
+import androidx.work.ExistingPeriodicWorkPolicy
 import androidx.work.ExistingWorkPolicy
-import androidx.work.OneTimeWorkRequest
+import androidx.work.OneTimeWorkRequestBuilder
+import androidx.work.PeriodicWorkRequestBuilder
 import androidx.work.WorkManager
 import io.flutter.embedding.engine.FlutterEngineCache
 import java.util.concurrent.TimeUnit
@@ -18,6 +20,7 @@ class BackgroundWorkerApiImpl(context: Context) : BackgroundWorkerFgHostApi {
 
   override fun enable() {
     enqueueMediaObserver(ctx)
+    enqueuePeriodicWorker(ctx)
   }
 
   override fun saveNotificationMessage(title: String, body: String) {
@@ -27,12 +30,14 @@ class BackgroundWorkerApiImpl(context: Context) : BackgroundWorkerFgHostApi {
   override fun configure(settings: BackgroundWorkerSettings) {
     BackgroundWorkerPreferences(ctx).updateSettings(settings)
     enqueueMediaObserver(ctx)
+    enqueuePeriodicWorker(ctx)
   }
 
   override fun disable() {
     WorkManager.getInstance(ctx).apply {
       cancelUniqueWork(OBSERVER_WORKER_NAME)
       cancelUniqueWork(BACKGROUND_WORKER_NAME)
+      cancelUniqueWork(PERIODIC_WORKER_NAME)
     }
     Log.i(TAG, "Cancelled background upload tasks")
   }
@@ -40,6 +45,7 @@ class BackgroundWorkerApiImpl(context: Context) : BackgroundWorkerFgHostApi {
   companion object {
     private const val BACKGROUND_WORKER_NAME = "immich/BackgroundWorkerV1"
     private const val OBSERVER_WORKER_NAME = "immich/MediaObserverV1"
+    private const val PERIODIC_WORKER_NAME = "immich/PeriodicBackgroundWorkerV1"
     const val ENGINE_CACHE_KEY = "immich::background_worker::engine"
 
 
@@ -55,7 +61,7 @@ class BackgroundWorkerApiImpl(context: Context) : BackgroundWorkerFgHostApi {
         setRequiresCharging(settings.requiresCharging)
       }.build()
 
-      val work = OneTimeWorkRequest.Builder(MediaObserver::class.java)
+      val work = OneTimeWorkRequestBuilder<MediaObserver>()
         .setConstraints(constraints)
         .build()
       WorkManager.getInstance(ctx)
@@ -67,10 +73,30 @@ class BackgroundWorkerApiImpl(context: Context) : BackgroundWorkerFgHostApi {
       )
     }
 
+    fun enqueuePeriodicWorker(ctx: Context) {
+      val settings = BackgroundWorkerPreferences(ctx).getSettings()
+      val constraints = Constraints.Builder().apply {
+        setRequiresCharging(settings.requiresCharging)
+      }.build()
+
+      val work =
+        PeriodicWorkRequestBuilder<PeriodicWorker>(
+          1,
+          TimeUnit.HOURS,
+          15,
+          TimeUnit.MINUTES
+        ).setConstraints(constraints)
+          .build()
+
+      WorkManager.getInstance(ctx)
+        .enqueueUniquePeriodicWork(PERIODIC_WORKER_NAME, ExistingPeriodicWorkPolicy.UPDATE, work)
+
+      Log.i(TAG, "Enqueued periodic background worker with name: $PERIODIC_WORKER_NAME")
+    }
+
     fun enqueueBackgroundWorker(ctx: Context) {
       val constraints = Constraints.Builder().setRequiresBatteryNotLow(true).build()
-
-      val work = OneTimeWorkRequest.Builder(BackgroundWorker::class.java)
+      val work = OneTimeWorkRequestBuilder<BackgroundWorker>()
         .setConstraints(constraints)
         .setBackoffCriteria(BackoffPolicy.EXPONENTIAL, 1, TimeUnit.MINUTES)
         .build()

mobile/android/app/src/main/kotlin/app/alextran/immich/background/PeriodicWorker.kt

@@ -0,0 +1,16 @@
+package app.alextran.immich.background
+
+import android.content.Context
+import android.util.Log
+import androidx.work.Worker
+import androidx.work.WorkerParameters
+
+class PeriodicWorker(context: Context, params: WorkerParameters) : Worker(context, params) {
+  private val ctx: Context = context.applicationContext
+
+  override fun doWork(): Result {
+    Log.i("PeriodicWorker", "Periodic worker triggered, starting background worker")
+    BackgroundWorkerApiImpl.enqueueBackgroundWorker(ctx)
+    return Result.success()
+  }
+}

mobile/android/fastlane/Fastfile

@@ -35,8 +35,8 @@ platform :android do
       task: 'bundle', 
       build_type: 'Release',
       properties: {
-        "android.injected.version.code" => 3024,
-        "android.injected.version.name" => "2.2.1",
+        "android.injected.version.code" => 3025,
+        "android.injected.version.name" => "2.2.2",
       }
     )
     upload_to_play_store(skip_upload_apk: true, skip_upload_images: true, skip_upload_screenshots: true, aab: '../build/app/outputs/bundle/release/app-release.aab')

mobile/ios/fastlane/Fastfile

@@ -169,7 +169,7 @@ platform :ios do
       targets: ["Runner", "ShareExtension", "WidgetExtension"]
     )
     increment_version_number(
-      version_number: "2.2.1"
+      version_number: "2.2.2"
     )
     increment_build_number(
       build_number: latest_testflight_build_number + 1,

mobile/lib/domain/services/sync_stream.service.dart

@@ -132,7 +132,8 @@ class SyncStreamService {
         return;
       // SyncCompleteV1 is used to signal the completion of the sync process. Cleanup stale assets and signal completion
       case SyncEntityType.syncCompleteV1:
-        return _syncStreamRepository.pruneAssets();
+        return;
+      // return _syncStreamRepository.pruneAssets();
       // Request to reset the client state. Clear everything related to remote entities
       case SyncEntityType.syncResetV1:
         return _syncStreamRepository.reset();

mobile/lib/infrastructure/repositories/sync_stream.repository.dart

@@ -612,15 +612,12 @@ class SyncStreamRepository extends DriftDatabaseRepository {
 
         final validUsers = {currentUserId, ...partnerIds.nonNulls};
 
-        // Asset is not owned by the current user or any of their partners and is not part of any (shared) album or memory
+        // Asset is not owned by the current user or any of their partners and is not part of any (shared) album
         // Likely a stale asset that was previously shared but has been removed
         await _db.remoteAssetEntity.deleteWhere((asset) {
           return asset.ownerId.isNotIn(validUsers) &
               asset.id.isNotInQuery(
                 _db.remoteAlbumAssetEntity.selectOnly()..addColumns([_db.remoteAlbumAssetEntity.assetId]),
-              ) &
-              asset.id.isNotInQuery(
-                _db.memoryAssetEntity.selectOnly()..addColumns([_db.memoryAssetEntity.assetId]),
               );
         });
       });

mobile/openapi/README.md

@@ -3,7 +3,7 @@ Immich API
 
 This Dart package is automatically generated by the [OpenAPI Generator](https://openapi-generator.tech) project:
 
-- API version: 2.2.1
+- API version: 2.2.2
 - Generator version: 7.8.0
 - Build package: org.openapitools.codegen.languages.DartClientCodegen
 

mobile/pubspec.yaml

@@ -2,7 +2,7 @@ name: immich_mobile
 description: Immich - selfhosted backup media file on mobile phone
 
 publish_to: 'none'
-version: 2.2.1+3024
+version: 2.2.2+3025
 
 environment:
   sdk: '>=3.8.0 <4.0.0'

mobile/test/infrastructure/repositories/sync_stream_prune_assets_test.dart

@@ -1,266 +0,0 @@
-import 'package:drift/native.dart';
-import 'package:flutter_test/flutter_test.dart';
-import 'package:immich_mobile/infrastructure/repositories/db.repository.dart';
-import 'package:immich_mobile/infrastructure/repositories/sync_stream.repository.dart';
-import 'package:openapi/api.dart';
-
-/// This test reproduces the bug where pruneAssets() deletes assets that are part of memories,
-/// causing foreign key constraint failures when trying to insert memory-asset relationships.
-void main() {
-  late DbRepository db;
-  late SyncStreamRepository sut;
-
-  setUp(() async {
-    db = DbRepository(NativeDatabase.memory());
-    sut = SyncStreamRepository(db);
-
-    // Set up test data: Create a user and a partner
-    await sut.updateAuthUsersV1([
-      SyncAuthUserV1(
-        email: 'current-user@test.com',
-        id: 'user-1',
-        isAdmin: false,
-        name: 'Current User',
-        avatarColor: null,
-        hasProfileImage: false,
-        profileChangedAt: DateTime(2025),
-      ),
-    ]);
-
-    await sut.updateUsersV1([
-      SyncUserV1(
-        deletedAt: null,
-        email: 'partner@test.com',
-        id: 'partner-1',
-        name: 'Partner User',
-        avatarColor: null,
-        hasProfileImage: false,
-        profileChangedAt: DateTime(2025),
-      ),
-    ]);
-
-    await sut.updatePartnerV1([
-      SyncPartnerV1(
-        inTimeline: true,
-        sharedById: 'partner-1',
-        sharedWithId: 'user-1',
-      ),
-    ]);
-  });
-
-  tearDown(() async {
-    await db.close();
-  });
-
-  group('pruneAssets - Memory Asset Bug', () {
-    test('BEFORE FIX: pruneAssets() should NOT delete assets that are part of memories', () async {
-      // Step 1: Create an asset owned by someone else (not current user or partner)
-      await sut.updateAssetsV1([
-        SyncAssetV1(
-          checksum: 'checksum-1'.codeUnits,
-          deletedAt: null,
-          deviceAssetId: 'device-1',
-          deviceId: 'device-1',
-          duplicateId: null,
-          duration: null,
-          fileCreatedAt: DateTime(2025, 1, 1),
-          fileModifiedAt: DateTime(2025, 1, 1),
-          id: 'asset-shared-memory',
-          isArchived: false,
-          isFavorite: false,
-          isOffline: false,
-          isTrashed: false,
-          libraryId: null,
-          livePhotoVideoId: null,
-          localDateTime: DateTime(2025, 1, 1),
-          originalFileName: 'shared-memory.jpg',
-          // Asset owned by someone else - should be pruned if not in album/memory
-          ownerId: 'other-user-not-partner',
-          resized: true,
-          stackId: null,
-          thumbhash: null,
-          type: AssetTypeEnum.IMAGE,
-          updatedAt: DateTime(2025, 1, 1),
-          visibility: AssetVisibility.public_,
-        ),
-      ]);
-
-      // Step 2: Create a memory owned by current user
-      await sut.updateMemoriesV1([
-        SyncMemoryV1(
-          createdAt: DateTime(2025, 1, 1),
-          data: {'year': 2025, 'title': 'Test Memory'},
-          deletedAt: null,
-          hideAt: null,
-          id: 'memory-1',
-          isSaved: false,
-          memoryAt: DateTime(2025, 1, 1),
-          ownerId: 'user-1',
-          seenAt: null,
-          showAt: DateTime(2025, 1, 1),
-          type: MemoryType.onThisDay,
-          updatedAt: DateTime(2025, 1, 1),
-        ),
-      ]);
-
-      // Step 3: Link the shared asset to the memory
-      await sut.updateMemoryAssetsV1([
-        SyncMemoryAssetV1(
-          assetId: 'asset-shared-memory',
-          memoryId: 'memory-1',
-        ),
-      ]);
-
-      // Verify the asset and memory-asset relationship exist
-      final assetsBefore = await db.remoteAssetEntity.select().get();
-      final memoryAssetsBefore = await db.memoryAssetEntity.select().get();
-      expect(assetsBefore.length, 1);
-      expect(assetsBefore.first.id, 'asset-shared-memory');
-      expect(memoryAssetsBefore.length, 1);
-
-      // Step 4: Call pruneAssets() - This is where the bug happens
-      await sut.pruneAssets();
-
-      // Step 5: Verify the asset is NOT deleted (because it's in a memory)
-      final assetsAfter = await db.remoteAssetEntity.select().get();
-      expect(
-        assetsAfter.length,
-        1,
-        reason: 'Asset should NOT be pruned because it is part of a memory',
-      );
-      expect(assetsAfter.first.id, 'asset-shared-memory');
-
-      // Step 6: Verify we can still work with memory-asset relationships
-      // This simulates receiving more sync events after pruning
-      await expectLater(
-        sut.updateMemoryAssetsV1([
-          SyncMemoryAssetV1(
-            assetId: 'asset-shared-memory',
-            memoryId: 'memory-1',
-          ),
-        ]),
-        completes,
-        reason: 'Should not throw foreign key constraint error',
-      );
-    });
-
-    test('pruneAssets() SHOULD delete assets not in albums or memories', () async {
-      // Step 1: Create an asset that's truly orphaned (not in album or memory)
-      await sut.updateAssetsV1([
-        SyncAssetV1(
-          checksum: 'checksum-2'.codeUnits,
-          deletedAt: null,
-          deviceAssetId: 'device-2',
-          deviceId: 'device-2',
-          duplicateId: null,
-          duration: null,
-          fileCreatedAt: DateTime(2025, 1, 1),
-          fileModifiedAt: DateTime(2025, 1, 1),
-          id: 'asset-orphaned',
-          isArchived: false,
-          isFavorite: false,
-          isOffline: false,
-          isTrashed: false,
-          libraryId: null,
-          livePhotoVideoId: null,
-          localDateTime: DateTime(2025, 1, 1),
-          originalFileName: 'orphaned.jpg',
-          ownerId: 'other-user-not-partner',
-          resized: true,
-          stackId: null,
-          thumbhash: null,
-          type: AssetTypeEnum.IMAGE,
-          updatedAt: DateTime(2025, 1, 1),
-          visibility: AssetVisibility.public_,
-        ),
-      ]);
-
-      // Verify the asset exists
-      final assetsBefore = await db.remoteAssetEntity.select().get();
-      expect(assetsBefore.length, 1);
-
-      // Call pruneAssets()
-      await sut.pruneAssets();
-
-      // Verify the orphaned asset IS deleted
-      final assetsAfter = await db.remoteAssetEntity.select().get();
-      expect(
-        assetsAfter.length,
-        0,
-        reason: 'Orphaned asset should be pruned',
-      );
-    });
-
-    test('pruneAssets() should NOT delete assets in albums', () async {
-      // Step 1: Create an asset and an album
-      await sut.updateAssetsV1([
-        SyncAssetV1(
-          checksum: 'checksum-3'.codeUnits,
-          deletedAt: null,
-          deviceAssetId: 'device-3',
-          deviceId: 'device-3',
-          duplicateId: null,
-          duration: null,
-          fileCreatedAt: DateTime(2025, 1, 1),
-          fileModifiedAt: DateTime(2025, 1, 1),
-          id: 'asset-in-album',
-          isArchived: false,
-          isFavorite: false,
-          isOffline: false,
-          isTrashed: false,
-          libraryId: null,
-          livePhotoVideoId: null,
-          localDateTime: DateTime(2025, 1, 1),
-          originalFileName: 'in-album.jpg',
-          ownerId: 'other-user-not-partner',
-          resized: true,
-          stackId: null,
-          thumbhash: null,
-          type: AssetTypeEnum.IMAGE,
-          updatedAt: DateTime(2025, 1, 1),
-          visibility: AssetVisibility.public_,
-        ),
-      ]);
-
-      await sut.updateAlbumsV1([
-        SyncAlbumV1(
-          albumName: 'Test Album',
-          albumThumbnailAssetId: null,
-          createdAt: DateTime(2025, 1, 1),
-          deletedAt: null,
-          description: 'Test',
-          id: 'album-1',
-          isActivityEnabled: false,
-          lastModifiedAssetTimestamp: DateTime(2025, 1, 1),
-          order: AlbumUserRole.editor,
-          ownerId: 'user-1',
-          startDate: DateTime(2025, 1, 1),
-          endDate: DateTime(2025, 1, 2),
-          updatedAt: DateTime(2025, 1, 1),
-        ),
-      ]);
-
-      await sut.updateAlbumToAssetsV1([
-        SyncAlbumToAssetV1(
-          albumId: 'album-1',
-          assetId: 'asset-in-album',
-        ),
-      ]);
-
-      // Verify setup
-      final assetsBefore = await db.remoteAssetEntity.select().get();
-      expect(assetsBefore.length, 1);
-
-      // Call pruneAssets()
-      await sut.pruneAssets();
-
-      // Verify asset is NOT deleted (protected by album membership)
-      final assetsAfter = await db.remoteAssetEntity.select().get();
-      expect(
-        assetsAfter.length,
-        1,
-        reason: 'Asset should NOT be pruned because it is in an album',
-      );
-    });
-  });
-}

open-api/immich-openapi-specs.json

@@ -10006,7 +10006,7 @@
   "info": {
     "title": "Immich",
     "description": "Immich API",
-    "version": "2.2.1",
+    "version": "2.2.2",
     "contact": {}
   },
   "tags": [],

open-api/typescript-sdk/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@immich/sdk",
-  "version": "2.2.1",
+  "version": "2.2.2",
   "description": "Auto-generated TypeScript SDK for the Immich API",
   "type": "module",
   "main": "./build/index.js",

open-api/typescript-sdk/src/fetch-client.ts

@@ -1,6 +1,6 @@
 /**
  * Immich
- * 2.2.1
+ * 2.2.2
  * DO NOT MODIFY - This file has been generated using oazapfts.
  * See https://www.npmjs.com/package/oazapfts
  */

server/package.json

@@ -1,6 +1,6 @@
 {
   "name": "immich",
-  "version": "2.2.1",
+  "version": "2.2.2",
   "description": "",
   "author": "",
   "private": true,

server/src/services/metadata.service.ts

@@ -236,8 +236,8 @@ export class MetadataService extends BaseService {
       latitude: number | null = null,
       longitude: number | null = null;
     if (this.hasGeo(exifTags)) {
-      latitude = exifTags.GPSLatitude;
-      longitude = exifTags.GPSLongitude;
+      latitude = Number(exifTags.GPSLatitude);
+      longitude = Number(exifTags.GPSLongitude);
       if (reverseGeocoding.enabled) {
         geo = await this.mapRepository.reverseGeocode({ latitude, longitude });
       }
@@ -894,12 +894,10 @@ export class MetadataService extends BaseService {
     };
   }
 
-  private hasGeo(tags: ImmichTags): tags is ImmichTags & { GPSLatitude: number; GPSLongitude: number } {
-    return (
-      tags.GPSLatitude !== undefined &&
-      tags.GPSLongitude !== undefined &&
-      (tags.GPSLatitude !== 0 || tags.GPSLatitude !== 0)
-    );
+  private hasGeo(tags: ImmichTags) {
+    const lat = Number(tags.GPSLatitude);
+    const lng = Number(tags.GPSLongitude);
+    return !Number.isNaN(lat) && !Number.isNaN(lng) && (lat !== 0 || lng !== 0);
   }
 
   private getAutoStackId(tags: ImmichTags | null): string | null {

web/package.json

@@ -1,6 +1,6 @@
 {
   "name": "immich-web",
-  "version": "2.2.1",
+  "version": "2.2.2",
   "license": "GNU Affero General Public License version 3",
   "type": "module",
   "scripts": {

web/src/lib/components/shared-components/search-bar/search-bar.svelte

@@ -30,10 +30,10 @@
   let showSuggestions = $state(false);
   let isSearchSuggestions = $state(false);
   let selectedId: string | undefined = $state();
-  let isFocus = $state(false);
   let close: (() => Promise<void>) | undefined;
 
   const listboxId = generateId();
+  const searchTypeId = generateId();
 
   onDestroy(() => {
     searchStore.isSearchEnabled = false;
@@ -161,12 +161,10 @@
 
   const openDropdown = () => {
     showSuggestions = true;
-    isFocus = true;
   };
 
   const closeDropdown = () => {
     showSuggestions = false;
-    isFocus = false;
     searchHistoryBox?.clearSelection();
   };
 
@@ -251,6 +249,7 @@
         aria-activedescendant={selectedId ?? ''}
         aria-expanded={showSuggestions && isSearchSuggestions}
         aria-autocomplete="list"
+        aria-describedby={searchTypeId}
         use:shortcuts={[
           { shortcut: { key: 'Escape' }, onShortcut: onEscape },
           { shortcut: { ctrl: true, shift: true, key: 'k' }, onShortcut: onFilterClick },
@@ -287,12 +286,12 @@
       />
     </div>
 
-    {#if isFocus}
+    {#if searchStore.isSearchEnabled}
       <div
-        class="absolute inset-y-0 flex items-center"
+        id={searchTypeId}
+        class="absolute inset-y-0 flex items-center end-16"
         class:max-md:hidden={value}
-        class:end-16={isFocus}
-        class:end-28={isFocus && value.length > 0}
+        class:end-28={value.length > 0}
       >
         <p
           class="bg-immich-primary text-white dark:bg-immich-dark-primary/90 dark:text-black/75 rounded-full px-3 py-1 text-xs"