mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-09-28 02:48:57 +03:00
Josh HawkinsandNicolas Mowen
70ce193e09
* build out system health pane * tweaks * fixes * fix notice link so it opens the correct camera * tweak language
109 lines
3.5 KiB
Python
109 lines
3.5 KiB
Python
"""Tests for folding loaded model devices per enrichment and emitting them."""
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import unittest
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from types import SimpleNamespace
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from frigate.config import FrigateConfig
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from frigate.embeddings.types import ENRICHMENT_FOR_MODEL_TYPE, fold_runtime_devices
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from frigate.stats.util import embeddings_stats
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class TestFoldRuntimeDevices(unittest.TestCase):
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def test_every_enrichment_model_type_is_mapped(self):
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self.assertEqual(
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set(ENRICHMENT_FOR_MODEL_TYPE),
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{
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"arcface",
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"facenet",
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"jina_v1",
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"jina_v2",
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"paddleocr",
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"yolov9_license_plate",
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},
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)
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def test_non_cpu_wins_within_an_enrichment(self):
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# jina v1 pins its text model to the CPU by design
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loaded = {
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"/m/jina_v1_text.onnx": ("jina_v1", "CPU"),
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"/m/jina_v1_vision.onnx": ("jina_v1", "OpenVINO GPU"),
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}
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self.assertEqual(
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fold_runtime_devices(loaded), {"semantic_search": "OpenVINO GPU"}
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)
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def test_all_cpu_stays_cpu(self):
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loaded = {
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"/m/jina_v1_text.onnx": ("jina_v1", "CPU"),
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"/m/jina_v1_vision.onnx": ("jina_v1", "CPU"),
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}
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self.assertEqual(fold_runtime_devices(loaded), {"semantic_search": "CPU"})
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def test_detector_models_are_ignored(self):
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loaded = {"/m/yolo.onnx": ("yolov9", "CUDA")}
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self.assertEqual(fold_runtime_devices(loaded), {})
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def test_lpr_and_face(self):
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loaded = {
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"/m/det.onnx": ("paddleocr", "CUDA"),
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"/m/rec.onnx": ("paddleocr", "CUDA"),
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"/m/arcface.onnx": ("arcface", "CPU"),
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}
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self.assertEqual(
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fold_runtime_devices(loaded), {"lpr": "CUDA", "face_recognition": "CPU"}
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)
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def _metrics(devices: dict[str, str]) -> SimpleNamespace:
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value = SimpleNamespace(value=0.0)
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return SimpleNamespace(
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image_embeddings_speed=value,
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image_embeddings_eps=value,
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text_embeddings_speed=value,
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text_embeddings_eps=value,
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face_rec_speed=value,
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face_rec_fps=value,
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alpr_speed=value,
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alpr_pps=value,
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yolov9_lpr_speed=value,
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yolov9_lpr_pps=value,
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review_desc_speed=value,
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review_desc_dps=value,
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object_desc_speed=value,
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object_desc_dps=value,
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classification_speeds={},
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classification_cps={},
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runtime_devices=devices,
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)
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class TestEmbeddingsStats(unittest.TestCase):
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def setUp(self):
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self.config = FrigateConfig(
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**{
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"mqtt": {"host": "mqtt"},
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"face_recognition": {"enabled": True},
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"cameras": {
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"front_door": {
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"ffmpeg": {
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"inputs": [
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{
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"path": "rtsp://10.0.0.1:554/video",
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"roles": ["detect"],
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}
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]
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}
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}
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},
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}
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)
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def test_devices_emitted_when_present(self):
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stats = embeddings_stats(self.config, _metrics({"face_recognition": "CUDA"}))
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self.assertEqual(stats["devices"], {"face_recognition": "CUDA"})
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self.assertIn("face_recognition_speed", stats)
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def test_devices_omitted_when_empty(self):
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stats = embeddings_stats(self.config, _metrics({}))
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self.assertNotIn("devices", stats)
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