mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-11-08 22:53:01 +03:00
Josh HawkinsandGitHub
4eb60af5a7
* 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.
70 lines
2.5 KiB
Python
70 lines
2.5 KiB
Python
"""Detection section: models, the detectors they run on, and inference speed."""
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import os
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from frigate.analytics.collectors.common import rate
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from frigate.analytics.context import ReportContext
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from frigate.analytics.schema import DetectionModel, DetectionSection, ModelSource
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from frigate.config.config import DEFAULT_MODEL
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from frigate.const import MODEL_CACHE_DIR
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from frigate.detectors.detector_config import DEFAULT_SCENE
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from frigate.detectors.detector_types import DetectorTypeEnum
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from frigate.detectors.device import runner_names
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# the paths FrigateConfig fills in for a model that sets none
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BUNDLED_MODEL_PATHS = frozenset(
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{"/cpu_model.tflite", "/edgetpu_model.tflite", str(DEFAULT_MODEL["path"])}
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)
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def model_source(path: str | None) -> ModelSource:
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"""Default, Frigate+ (a cached model next to its info file), or custom.
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Parsing rewrites plus://<id> to the model cache, so the prefix is gone by now.
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"""
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if path is None or path in BUNDLED_MODEL_PATHS:
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return ModelSource.default
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if path.startswith(f"{MODEL_CACHE_DIR}/") and os.path.isfile(f"{path}.json"):
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return ModelSource.plus
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return ModelSource.custom
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def collect(ctx: ReportContext) -> DetectionSection:
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"""Describe each configured model and its measured inference speed."""
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config = ctx.config
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detectors = ctx.stats.get("detectors", {})
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model_specs = [(model, config.devices_for_model(model)) for model in config.models]
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# FrigateApp.start_detectors names the processes in this same order
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names = iter(runner_names([spec for _, specs in model_specs for spec in specs]))
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models: list[DetectionModel] = []
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for model, specs in model_specs:
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speeds: list[float] = []
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for _ in specs:
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speed = detectors.get(next(names), {}).get("inference_speed")
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if isinstance(speed, int | float) and speed > 0:
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speeds.append(float(speed))
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models.append(
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DetectionModel(
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default=model.scene == DEFAULT_SCENE,
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detector=DetectorTypeEnum(specs[0].detector),
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devices=len(specs),
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model_type=model.model_type,
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input=f"{model.width}x{model.height}",
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source=model_source(model.path),
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inference_ms=rate(sum(speeds) / len(speeds)) if speeds else None,
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)
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)
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return DetectionSection(
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models=models,
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detection_fps=rate(ctx.stats.get("detection_fps")),
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skipped_fps=rate(ctx.stats.get("skipped_fps")),
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)
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