adapt analytics to free-form model scenes, split notice counts, and peewee 4

docs/static/frigate-analytics-schema.json

@@ -373,6 +373,7 @@
         "intel-qsv",
         "jetson",
         "rpi",
+        "apple-silicon",
         "other"
       ],
       "title": "DecodeFamily",
@@ -381,6 +382,12 @@
     "DetectionModel": {
       "additionalProperties": false,
       "properties": {
+        "default": {
+          "description": "Whether the model serves cameras that set no scene",
+          "title": "Default",
+          "type": "boolean",
+          "x-public": true
+        },
         "detector": {
           "$ref": "#/$defs/DetectorTypeEnum",
           "description": "Detector type the model runs on",
@@ -396,7 +403,7 @@
         "inference_ms": {
           "anyOf": [
             {
-              "minimum": 0.0,
+              "minimum": 0,
               "type": "number"
             },
             {
@@ -426,6 +433,7 @@
         }
       },
       "required": [
+        "default",
         "detector",
         "devices",
         "model_type",
@@ -441,26 +449,23 @@
       "properties": {
         "detection_fps": {
           "description": "Detections per second across cameras",
-          "minimum": 0.0,
+          "minimum": 0,
           "title": "Detection Fps",
           "type": "number",
           "x-public": true
         },
         "models": {
-          "additionalProperties": {
+          "description": "Detection models",
+          "items": {
             "$ref": "#/$defs/DetectionModel"
           },
-          "description": "Detection models keyed by scene",
-          "propertyNames": {
-            "$ref": "#/$defs/SceneEnum"
-          },
           "title": "Models",
-          "type": "object",
+          "type": "array",
           "x-public": true
         },
         "skipped_fps": {
           "description": "Frames per second skipped across cameras",
-          "minimum": 0.0,
+          "minimum": 0,
           "title": "Skipped Fps",
           "type": "number",
           "x-public": true
@@ -476,6 +481,7 @@
     },
     "DetectorTypeEnum": {
       "enum": [
+        "axelera",
         "axengine",
         "cpu",
         "deepx",
@@ -772,6 +778,7 @@
         "nvidia",
         "rockchip",
         "rpi",
+        "apple-silicon",
         "other"
       ],
       "title": "GpuVendor",
@@ -785,12 +792,14 @@
         "openvino:NPU",
         "onnx:amd",
         "onnx:nvidia",
+        "onnx:lighter",
         "tensorrt",
         "hailo",
         "memryx",
         "deepx",
         "rknn",
         "axengine",
+        "axelera",
         "synaptics",
         "cpu",
         "other"
@@ -945,6 +954,8 @@
       "enum": [
         "rpi-64-h264",
         "rpi-64-h265",
+        "apple-silicon-h264",
+        "apple-silicon-h265",
         "vaapi",
         "intel-qsv-h264",
         "intel-qsv-h265",
@@ -1091,10 +1102,17 @@
     "NoticeCounts": {
       "additionalProperties": false,
       "properties": {
-        "dismissals": {
+        "acknowledgements": {
-          "description": "Dismissals since the last accepted report",
+          "description": "Acknowledgements since the last accepted report",
           "minimum": 0,
-          "title": "Dismissals",
+          "title": "Acknowledgements",
+          "type": "integer",
+          "x-public": true
+        },
+        "mutes": {
+          "description": "Mutes since the last accepted report",
+          "minimum": 0,
+          "title": "Mutes",
           "type": "integer",
           "x-public": true
         },
@@ -1108,7 +1126,8 @@
       },
       "required": [
         "occurrences",
-        "dismissals"
+        "acknowledgements",
+        "mutes"
       ],
       "title": "NoticeCounts",
       "type": "object"
@@ -1118,7 +1137,10 @@
         "detector_stuck",
         "model_download_failed",
         "skipped_detections",
+        "ffmpeg_high_cpu",
+        "detect_high_cpu",
         "shm_too_low",
+        "object_processing_behind",
         "failed_login"
       ],
       "title": "NoticeKindKey",
@@ -1195,18 +1217,6 @@
       "title": "RetainDays",
       "type": "object"
     },
-    "SceneEnum": {
-      "description": "The camera environment a detection model is intended for.",
-      "enum": [
-        "all",
-        "indoor",
-        "outdoor",
-        "indoor_thermal",
-        "outdoor_thermal"
-      ],
-      "title": "SceneEnum",
-      "type": "string"
-    },
     "SemanticSearchModel": {
       "enum": [
         "jinav1",

frigate/analytics/collectors/detection.py

@@ -7,7 +7,7 @@ from frigate.analytics.context import ReportContext
 from frigate.analytics.schema import DetectionModel, DetectionSection, ModelSource
 from frigate.config.config import DEFAULT_MODEL
 from frigate.const import MODEL_CACHE_DIR
-from frigate.detectors.detector_config import SceneEnum
+from frigate.detectors.detector_config import DEFAULT_SCENE
 from frigate.detectors.detector_types import DetectorTypeEnum
 from frigate.detectors.device import runner_names
 
@@ -38,7 +38,7 @@ def collect(ctx: ReportContext) -> DetectionSection:
 
     # FrigateApp.start_detectors names the processes in this same order
     names = iter(runner_names([spec for _, specs in model_specs for spec in specs]))
-    models: dict[SceneEnum, DetectionModel] = {}
+    models: list[DetectionModel] = []
 
     for model, specs in model_specs:
         speeds: list[float] = []
@@ -49,13 +49,16 @@ def collect(ctx: ReportContext) -> DetectionSection:
             if isinstance(speed, int | float) and speed > 0:
                 speeds.append(float(speed))
 
-        models[model.scene] = DetectionModel(
+        models.append(
-            detector=DetectorTypeEnum(specs[0].detector),
+            DetectionModel(
-            devices=len(specs),
+                default=model.scene == DEFAULT_SCENE,
-            model_type=model.model_type,
+                detector=DetectorTypeEnum(specs[0].detector),
-            input=f"{model.width}x{model.height}",
+                devices=len(specs),
-            source=model_source(model.path),
+                model_type=model.model_type,
-            inference_ms=rate(sum(speeds) / len(speeds)) if speeds else None,
+                input=f"{model.width}x{model.height}",
+                source=model_source(model.path),
+                inference_ms=rate(sum(speeds) / len(speeds)) if speeds else None,
+            )
         )
 
     return DetectionSection(

frigate/analytics/collectors/health.py

@@ -32,11 +32,14 @@ def notice_deltas(notice_stats: list[dict[str, Any]]) -> dict[Any, NoticeCounts]
             continue
 
         occurrences = max(row["occurrences"] - row["reported_occurrences"], 0)
-        dismissals = max(row["dismissals"] - row["reported_dismissals"], 0)
+        acknowledgements = max(
+            row["acknowledgements"] - row["reported_acknowledgements"], 0
+        )
+        mutes = max(row["mutes"] - row["reported_mutes"], 0)
 
-        if occurrences or dismissals:
+        if occurrences or acknowledgements or mutes:
             deltas[NoticeKindKey(row["kind"])] = NoticeCounts(
-                occurrences=occurrences, dismissals=dismissals
+                occurrences=occurrences, acknowledgements=acknowledgements, mutes=mutes
             )
 
     return deltas

frigate/analytics/schema.py

@@ -13,7 +13,7 @@ from frigate.config.camera.birdseye import BirdseyeModeEnum
 from frigate.config.camera.camera import CameraTypeEnum
 from frigate.config.camera.genai import GenAIProviderEnum, GenAIRoleEnum
 from frigate.config.classification import ModelSizeEnum
-from frigate.detectors.detector_config import ModelTypeEnum, SceneEnum
+from frigate.detectors.detector_config import ModelTypeEnum
 from frigate.detectors.detector_types import DetectorTypeEnum
 from frigate.ffmpeg_presets import PRESETS_HW_ACCEL_DECODE, PRESETS_INPUT
 from frigate.notices.types import NOTICE_KINDS
@@ -53,6 +53,7 @@ class GpuVendor(StrEnum):
     nvidia = "nvidia"
     rockchip = "rockchip"
     rpi = "rpi"
+    apple_silicon = "apple-silicon"
     other = "other"
 
 
@@ -63,6 +64,7 @@ class DecodeFamily(StrEnum):
     intel_qsv = "intel-qsv"
     jetson = "jetson"
     rpi = "rpi"
+    apple_silicon = "apple-silicon"
     other = "other"
 
 
@@ -73,12 +75,14 @@ class HardwareKey(StrEnum):
     openvino_npu = "openvino:NPU"
     onnx_amd = "onnx:amd"
     onnx_nvidia = "onnx:nvidia"
+    onnx_lighter = "onnx:lighter"
     tensorrt = "tensorrt"
     hailo = "hailo"
     memryx = "memryx"
     deepx = "deepx"
     rknn = "rknn"
     axengine = "axengine"
+    axelera = "axelera"
     synaptics = "synaptics"
     cpu = "cpu"
     other = "other"
@@ -228,6 +232,7 @@ class HardwareSection(AnalyticsModel):
 
 
 class DetectionModel(AnalyticsModel):
+    default: bool = metric("Whether the model serves cameras that set no scene")
     detector: DetectorTypeEnum = metric("Detector type the model runs on")
     devices: int = count("Devices the model runs on")
     model_type: ModelTypeEnum = metric("Model architecture")
@@ -240,7 +245,7 @@ class DetectionModel(AnalyticsModel):
 
 
 class DetectionSection(AnalyticsModel):
-    models: dict[SceneEnum, DetectionModel] = metric("Detection models keyed by scene")
+    models: list[DetectionModel] = metric("Detection models")
     detection_fps: float = metric("Detections per second across cameras", ge=0)
     skipped_fps: float = metric("Frames per second skipped across cameras", ge=0)
 
@@ -369,7 +374,8 @@ class FeaturesSection(AnalyticsModel):
 
 class NoticeCounts(AnalyticsModel):
     occurrences: int = count("Occurrences since the last accepted report")
-    dismissals: int = count("Dismissals since the last accepted report")
+    acknowledgements: int = count("Acknowledgements since the last accepted report")
+    mutes: int = count("Mutes since the last accepted report")
 
 
 class HealthSection(AnalyticsModel):

frigate/models.py

@@ -209,7 +209,7 @@ class NoticeStats(Model):
     mutes = IntegerField(default=0)
     first_seen = DateTimeField()
     last_seen = DateTimeField()
-    # watermarks for a future analytics reporter; unused until then
+    # counts the last accepted analytics report covered
     reported_occurrences = IntegerField(default=0)
     reported_acknowledgements = IntegerField(default=0)
     reported_mutes = IntegerField(default=0)

frigate/notices/registry.py

@@ -395,7 +395,8 @@ class NoticeRegistry:
             for row in snapshot:
                 NoticeStats.update(
                     reported_occurrences=row["occurrences"],
-                    reported_dismissals=row["dismissals"],
+                    reported_acknowledgements=row["acknowledgements"],
+                    reported_mutes=row["mutes"],
                 ).where(NoticeStats.kind == row["kind"]).execute()
 
     def _write_repeats(

frigate/test/test_analytics_collectors_detection.py

@@ -7,7 +7,6 @@ from unittest.mock import patch
 
 from frigate.analytics.collectors import detection
 from frigate.analytics.schema import ModelSource
-from frigate.detectors.detector_config import SceneEnum
 from frigate.test.analytics_helpers import make_config, make_context
 
 
@@ -25,7 +24,8 @@ class TestDetectionCollector(unittest.TestCase):
 
         section = detection.collect(make_context(config, stats))
 
-        model = section.models[SceneEnum.all]
+        [model] = section.models
+        self.assertTrue(model.default)
         self.assertEqual(model.detector, "cpu")
         self.assertEqual(model.devices, 2)
         self.assertEqual(model.model_type, "ssd")
@@ -35,10 +35,29 @@ class TestDetectionCollector(unittest.TestCase):
         self.assertEqual(section.detection_fps, 12.35)
         self.assertEqual(section.skipped_fps, 0.0)
 
+    def test_named_scene_reports_no_name(self):
+        config = make_config(
+            {
+                "models": [
+                    {"devices": ["cpu"]},
+                    {
+                        "scene": "backyard_thermal",
+                        "devices": ["cpu"],
+                        "path": "/thermal.tflite",
+                    },
+                ]
+            }
+        )
+
+        section = detection.collect(make_context(config))
+
+        self.assertEqual([m.default for m in section.models], [True, False])
+        self.assertNotIn("backyard_thermal", section.model_dump_json())
+
     def test_inference_is_null_before_the_first_stats(self):
         section = detection.collect(make_context())
 
-        self.assertIsNone(section.models[SceneEnum.all].inference_ms)
+        self.assertIsNone(section.models[0].inference_ms)
 
     def test_model_source(self):
         with tempfile.TemporaryDirectory() as cache:

frigate/test/test_analytics_collectors_features.py

@@ -4,8 +4,8 @@ import logging
 import os
 import unittest
 
+from peewee import SqliteDatabase
 from peewee_migrate import Router
-from playhouse.sqlite_ext import SqliteExtDatabase
 from playhouse.sqliteq import SqliteQueueDatabase
 
 from frigate.analytics.collectors import features
@@ -49,7 +49,7 @@ CONFIG = {
 
 class TestFeaturesCollector(unittest.TestCase):
     def setUp(self):
-        migrate_db = SqliteExtDatabase(TEST_DB)
+        migrate_db = SqliteDatabase(TEST_DB)
         del logging.getLogger("peewee_migrate").handlers[:]
         Router(migrate_db).run()
         migrate_db.close()

frigate/test/test_analytics_collectors_health.py

@@ -21,23 +21,29 @@ class TestHealthCollector(unittest.TestCase):
             {
                 "kind": "detector_stuck",
                 "occurrences": 5,
-                "dismissals": 1,
+                "acknowledgements": 1,
+                "mutes": 0,
                 "reported_occurrences": 3,
-                "reported_dismissals": 1,
+                "reported_acknowledgements": 1,
+                "reported_mutes": 0,
             },
             {
                 "kind": "shm_too_low",
                 "occurrences": 2,
-                "dismissals": 0,
+                "acknowledgements": 0,
+                "mutes": 0,
                 "reported_occurrences": 2,
-                "reported_dismissals": 0,
+                "reported_acknowledgements": 0,
+                "reported_mutes": 0,
             },
             {
                 "kind": "update_available",
                 "occurrences": 4,
-                "dismissals": 0,
+                "acknowledgements": 0,
+                "mutes": 0,
                 "reported_occurrences": 0,
-                "reported_dismissals": 0,
+                "reported_acknowledgements": 0,
+                "reported_mutes": 0,
             },
         ]
 
@@ -49,10 +55,10 @@ class TestHealthCollector(unittest.TestCase):
         self.assertTrue(section.retention_unmet)
         self.assertEqual(
             {
-                kind: (c.occurrences, c.dismissals)
+                kind: (c.occurrences, c.acknowledgements, c.mutes)
                 for kind, c in section.notices.items()
             },
-            {"detector_stuck": (2, 0)},
+            {"detector_stuck": (2, 0, 0)},
         )
 
     def test_missing_stats_give_zeros(self):

frigate/test/test_analytics_report.py

@@ -6,8 +6,8 @@ import os
 import unittest
 from unittest.mock import Mock, patch
 
+from peewee import SqliteDatabase
 from peewee_migrate import Router
-from playhouse.sqlite_ext import SqliteExtDatabase
 from playhouse.sqliteq import SqliteQueueDatabase
 
 from frigate.analytics import report
@@ -50,7 +50,7 @@ class TestBuildReport(unittest.TestCase):
 
 class TestRealCollectors(unittest.TestCase):
     def setUp(self):
-        migrate_db = SqliteExtDatabase(TEST_DB)
+        migrate_db = SqliteDatabase(TEST_DB)
         del logging.getLogger("peewee_migrate").handlers[:]
         Router(migrate_db).run()
         migrate_db.close()

frigate/test/test_analytics_reporter.py

@@ -24,9 +24,11 @@ SNAPSHOT = [
     {
         "kind": "detector_stuck",
         "occurrences": 3,
-        "dismissals": 0,
+        "acknowledgements": 0,
+        "mutes": 0,
         "reported_occurrences": 1,
-        "reported_dismissals": 0,
+        "reported_acknowledgements": 0,
+        "reported_mutes": 0,
     }
 ]
 

frigate/test/test_notice_registry.py

@@ -372,7 +372,8 @@ class TestMarkReported(RegistryTestCase):
         row = self.registry.stats()[0]
         self.assertEqual(row["occurrences"], 2)
         self.assertEqual(row["reported_occurrences"], 1)
-        self.assertEqual(row["reported_dismissals"], 0)
+        self.assertEqual(row["reported_acknowledgements"], 0)
+        self.assertEqual(row["reported_mutes"], 0)
 
 
 class TestApply(RegistryTestCase):