fix untrained classification models not saving images

The mypy cleanup in https://github.com/blakeblackshear/frigate/pull/22658 added a check on the tensor details to the top of process_frame for both state and object models. Those are unset until a model is trained, so untrained models returned early and never saved images to Recent Classifications. Remove the check from process_frame, the classify methods already check the tensor details before using them.

docs/docs/configuration/genai/config.md

@@ -73,9 +73,10 @@ You must use a vision-capable model with Frigate. The following models are recom
 
 The `embeddings` role needs a different kind of model. Text queries are matched against the stored image embeddings, so the model must be trained to place images and text into the same vector space. A chat or description model will still return vectors when asked, but those vectors are not trained for retrieval and text searches will return poor matches with no error to indicate why.
 
-| Model                | Notes                                                                                                                                                               |
-| -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Must be served by llama.cpp started with `--embeddings` and `--mmproj`. |
+| Model                | Notes                                                                                                                                                                  |
+| -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `embeddinggemma-2`   | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Strong semantic search accuracy with efficient inference on a small model. |
+| `qwen3-vl-embedding` | Multimodal embeddings for [Semantic Search](/configuration/semantic_search#genai-provider). Good performance, large model that requires strong hardware for inference. |
 
 :::info
 

frigate/api/camera.py

@@ -35,7 +35,11 @@ from frigate.config.camera.updater import (
 )
 from frigate.config.env import substitute_frigate_vars
 from frigate.models import User
-from frigate.util.builtin import clean_camera_user_pass, get_record_segment_time
+from frigate.util.builtin import (
+    clean_camera_user_pass,
+    clear_orphaned_comments,
+    get_record_segment_time,
+)
 from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
 from frigate.util.config import find_config_file
 from frigate.util.image import run_ffmpeg_snapshot
@@ -1201,6 +1205,7 @@ async def delete_camera(
                 # Remove camera from config
                 if "cameras" in data and camera_name in data["cameras"]:
                     del data["cameras"][camera_name]
+                    clear_orphaned_comments(data["cameras"], data, "cameras")
 
                 # Remove camera from auth roles
                 auth = data.get("auth", {})

frigate/api/media.py

@@ -351,8 +351,13 @@ async def get_snapshot_from_recording(
         mime_type = "png" if format == "png" else "jpeg"
         config: FrigateConfig = request.app.frigate_config
 
-        image_data = get_image_from_recording(
-            config.ffmpeg, recording.path, time_in_segment, codec, height
+        image_data = await asyncio.to_thread(
+            get_image_from_recording,
+            config.ffmpeg,
+            recording.path,
+            time_in_segment,
+            codec,
+            height,
         )
 
         if not image_data:
@@ -406,8 +411,12 @@ async def submit_recording_snapshot_to_plus(
         config: FrigateConfig = request.app.frigate_config
         recording: Recordings = recording_query.get()
         time_in_segment = frame_time - recording.start_time
-        image_data = get_image_from_recording(
-            config.ffmpeg, recording.path, time_in_segment, "png"
+        image_data = await asyncio.to_thread(
+            get_image_from_recording,
+            config.ffmpeg,
+            recording.path,
+            time_in_segment,
+            "png",
         )
 
         if not image_data:

frigate/data_processing/real_time/custom_classification.py

@@ -170,12 +170,7 @@ class CustomStateClassificationProcessor(DeferredRealtimeProcessorApi):
         return None
 
     def process_frame(self, frame_data: dict[str, Any], frame: np.ndarray) -> None:
-        if (
-            not self.model_config.name
-            or not self.model_config.state_config
-            or not self.tensor_input_details
-            or not self.tensor_output_details
-        ):
+        if not self.model_config.name or not self.model_config.state_config:
             return
 
         if self.metrics and self.model_config.name in self.metrics.classification_cps:
@@ -515,12 +510,7 @@ class CustomObjectClassificationProcessor(DeferredRealtimeProcessorApi):
         return best_label, avg_score
 
     def process_frame(self, obj_data: dict[str, Any], frame: np.ndarray) -> None:
-        if (
-            not self.model_config.name
-            or not self.model_config.object_config
-            or not self.tensor_input_details
-            or not self.tensor_output_details
-        ):
+        if not self.model_config.name or not self.model_config.object_config:
             return
 
         if self.metrics and self.model_config.name in self.metrics.classification_cps:

frigate/test/http_api/test_http_media.py

@@ -1,6 +1,9 @@
 """Unit tests for recordings/media API endpoints."""
 
+import threading
+from concurrent.futures import ThreadPoolExecutor
 from datetime import UTC, datetime
+from unittest.mock import patch
 
 import pytz
 from fastapi import Request
@@ -527,3 +530,90 @@ class TestHttpMedia(BaseTestHttp):
 
             assert response.status_code == 200
             assert response.json() == [{"start_time": 1010, "end_time": 1030}]
+
+    def _insert_recording(self, id: str, start_time: float, end_time: float) -> None:
+        Recordings.insert(
+            id=id,
+            path=f"/media/recordings/{id}.mp4",
+            camera="front_door",
+            start_time=start_time,
+            end_time=end_time,
+            duration=end_time - start_time,
+            motion=0,
+        ).execute()
+
+    def test_recording_snapshot_does_not_block_event_loop(self):
+        self._insert_recording("snapshot", 1000, 1010)
+        started = threading.Event()
+        release = threading.Event()
+        finished = threading.Event()
+
+        def slow_image(*args):
+            started.set()
+            release.wait(timeout=5)
+            finished.set()
+            return b"jpeg"
+
+        with (
+            AuthTestClient(self.app) as client,
+            patch("frigate.api.media.get_image_from_recording", slow_image),
+            ThreadPoolExecutor(max_workers=1) as executor,
+        ):
+            snapshot = executor.submit(
+                client.get, "/front_door/recordings/1005/snapshot.jpg"
+            )
+            self.assertTrue(started.wait(timeout=2))
+            version = client.get("/version")
+            blocked = finished.is_set()
+            release.set()
+
+            self.assertEqual(version.status_code, 200)
+            self.assertFalse(blocked)
+            self.assertEqual(snapshot.result().status_code, 200)
+
+    def test_recording_snapshot_hit_returns_image(self):
+        self._insert_recording("snapshot", 1000, 1010)
+
+        with (
+            AuthTestClient(self.app) as client,
+            patch("frigate.api.media.get_image_from_recording", return_value=b"jpeg"),
+        ):
+            response = client.get("/front_door/recordings/1005/snapshot.jpg")
+
+        self.assertEqual(response.status_code, 200)
+        self.assertEqual(response.headers["Content-Type"], "image/jpeg")
+        self.assertEqual(response.content, b"jpeg")
+
+    def test_recording_snapshot_misses_return_404(self):
+        self._insert_recording("snapshot", 1000, 1010)
+
+        with AuthTestClient(self.app) as client:
+            absent = client.get("/front_door/recordings/2000/snapshot.jpg")
+            rounded_miss = client.get("/front_door/recordings/1010.5/snapshot.jpg")
+
+        self.assertEqual(absent.status_code, 404)
+        self.assertEqual(rounded_miss.status_code, 404)
+
+    def test_plus_snapshot_miss_returns_404_without_image_lookup(self):
+        with (
+            AuthTestClient(self.app) as client,
+            patch("frigate.api.media.get_image_from_recording") as image,
+        ):
+            response = client.post("/front_door/plus/1005")
+
+        self.assertEqual(response.status_code, 404)
+        image.assert_not_called()
+
+    def test_plus_snapshot_hit_uploads_image(self):
+        self._insert_recording("snapshot", 1000, 1010)
+
+        with (
+            AuthTestClient(self.app) as client,
+            patch("frigate.api.media.get_image_from_recording", return_value=b"png"),
+            patch("frigate.api.media.cv2.imdecode", return_value="frame"),
+            patch.object(self.app.frigate_config.plus_api, "upload_image") as upload,
+        ):
+            response = client.post("/front_door/plus/1005")
+
+        self.assertEqual(response.status_code, 200)
+        upload.assert_called_once_with("frame", "front_door")

frigate/test/test_update_yaml.py

@@ -6,7 +6,7 @@ import unittest
 
 from ruamel.yaml import YAML
 
-from frigate.util.builtin import update_yaml_file_bulk
+from frigate.util.builtin import clear_orphaned_comments, update_yaml_file_bulk
 
 
 class TestUpdateYaml(unittest.TestCase):
@@ -178,6 +178,27 @@ class TestUpdateYaml(unittest.TestCase):
         assert data["cameras"]["cam1"]["detect"]["fps"] == 5
         assert "# tuned for the pi" in self._read()
 
+    def test_delete_only_camera_with_comment_on_cameras_key(self):
+        """Deleting the only camera stays parseable when the cameras key
+        carries the default config's trailing comment."""
+        self._write(
+            "cameras: # No cameras defined, UI wizard should be used\n"
+            "  cam1:\n"
+            "    enabled: true\n"
+            "version: 0.18-0\n"
+        )
+        yaml = YAML()
+        with open(self.config_path) as f:
+            data = yaml.load(f)
+        del data["cameras"]["cam1"]
+        clear_orphaned_comments(data["cameras"], data, "cameras")
+        with open(self.config_path, "w") as f:
+            yaml.dump(data, f)
+
+        data = self._load()
+        assert data["cameras"] == {}
+        assert data["version"] == "0.18-0"
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=2)

web/src/components/overlay/CameraInfoDialog.tsx

@@ -91,7 +91,7 @@ export default function CameraInfoDialog({
         open={showCameraInfoDialog}
         onOpenChange={setShowCameraInfoDialog}
       >
-        <DialogContent>
+        <DialogContent className="scrollbar-container max-h-[90dvh] overflow-y-auto">
           <DialogHeader>
             <DialogTitle className="smart-capitalize">
               {t("cameras.info.cameraProbeInfo", {