Files
frigate/frigate/test/test_analytics_collectors_detection.py
T
Josh HawkinsandGitHub 4eb60af5a7 Implement opt-in analytics (#24440)
* Add analytics opt-in setting, prompt notice kind, and notice watermarks

* Add the analytics report schema

* Add the analytics state file

* Add the install and hardware analytics collectors

* Add the detection analytics collector

* Add the cameras analytics collector

* Add the features analytics collector

* Add the health analytics collector

* Build analytics reports from the section collectors

* Add the analytics report transport

* Send the daily analytics report from the main process

* Add the analytics preview API

* Generate the analytics schema and check it in CI

* Record the image variant in each Dockerfile

* Show the analytics preview in telemetry settings

* Document anonymous analytics

* change wording

* fixes

* update network requirements docs

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

* fixes

* change log levels

* docstrings

* docstrings

* honor file-only analytics opt-outs and skip pre-consent notices

An opt-out saved through the YAML editor's "Save only" or a hand edit never reached the live config, so reports kept going out under the old install ID until a restart. The reporter now reads telemetry.analytics from the config file when a report is due, validated with TelemetryConfig so yes, on, and 1 still count as consent, and an opt-out there deletes the state file and skips the send. The first report under a new install ID also carried every notice since the counters started, including ones from before the opt-in, so a fresh state file now resets the notice watermarks before the report's snapshot.

* take the notice baseline at opt-in instead of the first send

The watermark reset ran at the first send attempt, so notices raised between the opt-in and that send, up to 45 minutes after a startup, were absorbed into the reset and never reported. The reporter now writes the new install ID and resets the watermarks as soon as it sees consent without a state file.

* report notice counts cumulatively from a database baseline

Moving watermarks after each accepted send kept the install ID and the notice baseline out of step: pre-consent notices went out, notices raised before the first send were dropped, and a send that finished after an off/on toggle overwrote the new identity's baseline. health.notices now carries cumulative counts since the install ID was created. Creating an ID copies the lifetime counts into the existing reported_* columns before the state file names it, and nothing is written after a send, so the backend diffs consecutive reports per install ID.

* write held notice repeats before the analytics baseline reset

Repeats of batched kinds like failed_login wait in memory until the stats emitter flushes them, so a baseline reset taken while some were held left them out, and the next flush counted those pre-opt-in repeats as post-consent. The reset now writes held repeats to the notice history under the same lock before copying the counts.

* seed detector inference speed from the first inference

The average started at 0 so idle detectors read 0, but that made every detector's speed climb from 0 for its first couple dozen inferences after a start. Detectors now use the same InferenceSpeed helper as enrichments, so the first inference seeds the average and idle detectors still read 0.
2026-11-06 07:43:38 -07:00

88 lines
3.1 KiB
Python

"""Tests for the detection collector."""
import os
import tempfile
import unittest
from unittest.mock import patch
from frigate.analytics.collectors import detection
from frigate.analytics.schema import ModelSource
from frigate.test.analytics_helpers import make_config, make_context
class TestDetectionCollector(unittest.TestCase):
def test_reports_each_model_with_its_mean_inference_speed(self):
config = make_config({"models": [{"devices": ["cpu", "cpu"]}]})
stats = {
"detectors": {
"cpu": {"inference_speed": 10.0},
"cpu#2": {"inference_speed": 20.0},
},
"detection_fps": 12.346,
"skipped_fps": 0,
}
section = detection.collect(make_context(config, stats))
[model] = section.models
self.assertTrue(model.default)
self.assertEqual(model.detector, "cpu")
self.assertEqual(model.devices, 2)
self.assertEqual(model.model_type, "ssd")
self.assertEqual(model.input, "320x320")
self.assertEqual(model.source, ModelSource.default)
self.assertEqual(model.inference_ms, 15.0)
self.assertEqual(section.detection_fps, 12.35)
self.assertEqual(section.skipped_fps, 0.0)
def test_idle_detector_reports_no_speed(self):
config = make_config({"models": [{"devices": ["cpu"]}]})
stats = {"detectors": {"cpu": {"inference_speed": 0.0}}}
[model] = detection.collect(make_context(config, stats)).models
self.assertIsNone(model.inference_ms)
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[0].inference_ms)
def test_model_source(self):
with tempfile.TemporaryDirectory() as cache:
plus_model = os.path.join(cache, "abc123")
open(f"{plus_model}.json", "w").close()
with patch.object(detection, "MODEL_CACHE_DIR", cache):
self.assertEqual(detection.model_source(plus_model), ModelSource.plus)
self.assertEqual(
detection.model_source(os.path.join(cache, "no_info")),
ModelSource.custom,
)
self.assertEqual(detection.model_source(None), ModelSource.default)
self.assertEqual(
detection.model_source("/cpu_model.tflite"), ModelSource.default
)
self.assertEqual(
detection.model_source("/config/yolo.onnx"), ModelSource.custom
)