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Cleanup

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This commit is contained in:
Nicolas Mowen 2025-09-25 07:19:32 -06:00
parent a93c1e5653
commit 2a40e3d9ab
3 changed files with 89 additions and 91 deletions
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3
frigate/track/norfair_tracker.py
View File

@ -5,7 +5,6 @@ from typing import Any, Sequence, cast
import cv2
import numpy as np
from frigate.track.stationary_classifier import StationaryMotionClassifier
from norfair.drawing.draw_boxes import draw_boxes
from norfair.drawing.drawer import Drawable, Drawer
from norfair.filter import OptimizedKalmanFilterFactory
@ -13,12 +12,12 @@ from norfair.tracker import Detection, TrackedObject, Tracker
from rich import print
from rich.console import Console
from rich.table import Table
from scipy.ndimage import gaussian_filter
from frigate.camera import PTZMetrics
from frigate.config import CameraConfig
from frigate.ptz.autotrack import PtzMotionEstimator
from frigate.track import ObjectTracker
from frigate.track.stationary_classifier import StationaryMotionClassifier
from frigate.util.image import (
SharedMemoryFrameManager,
get_histogram,

6
frigate/track/stationary_classifier.py
View File

@ -80,7 +80,7 @@ class StationaryMotionClassifier:
y1,
x2,
y2,
crop.shape if 'crop' in locals() else None,
crop.shape if "crop" in locals() else None,
)
return result
@ -115,9 +115,7 @@ class StationaryMotionClassifier:
"""
if id not in self.anchor_crops or id not in self.anchor_boxes:
logger.debug(
"evaluate: id=%s has no anchor; default keep stationary", id
)
logger.debug("evaluate: id=%s has no anchor; default keep stationary", id)
return True
# Compare same spatial region across frames

171
notebooks/YOLO_NAS_Pretrained_Export.ipynb
View File

@ -1,88 +1,89 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "rmuF9iKWTbdk"
},
"outputs": [],
"source": [
"! pip install -q git+https://github.com/Deci-AI/super-gradients.git"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "NiRCt917KKcL"
},
"outputs": [],
"source": [
"! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.12/dist-packages/super_gradients/training/pretrained_models.py\n",
"! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.12/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "dTB0jy_NNSFz"
},
"outputs": [],
"source": [
"from super_gradients.common.object_names import Models\n",
"from super_gradients.conversion import DetectionOutputFormatMode\n",
"from super_gradients.training import models\n",
"\n",
"model = models.get(Models.YOLO_NAS_S, pretrained_weights=\"coco\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "GymUghyCNXem"
},
"outputs": [],
"source": [
"# export the model for compatibility with Frigate\n",
"\n",
"model.export(\"yolo_nas_s.onnx\",\n",
" output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
" max_predictions_per_image=20,\n",
" num_pre_nms_predictions=300,\n",
" confidence_threshold=0.4,\n",
" input_image_shape=(320,320),\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "uBhXV5g4Nh42"
},
"outputs": [],
"source": [
"from google.colab import files\n",
"\n",
"files.download('yolo_nas_s.onnx')"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "rmuF9iKWTbdk"
},
"outputs": [],
"source": [
"! pip install -q git+https://github.com/Deci-AI/super-gradients.git"
]
},
"nbformat": 4,
"nbformat_minor": 0
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "NiRCt917KKcL"
},
"outputs": [],
"source": [
"! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.12/dist-packages/super_gradients/training/pretrained_models.py\n",
"! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.12/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "dTB0jy_NNSFz"
},
"outputs": [],
"source": [
"from super_gradients.common.object_names import Models\n",
"from super_gradients.conversion import DetectionOutputFormatMode\n",
"from super_gradients.training import models\n",
"\n",
"model = models.get(Models.YOLO_NAS_S, pretrained_weights=\"coco\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "GymUghyCNXem"
},
"outputs": [],
"source": [
"# export the model for compatibility with Frigate\n",
"\n",
"model.export(\n",
" \"yolo_nas_s.onnx\",\n",
" output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
" max_predictions_per_image=20,\n",
" num_pre_nms_predictions=300,\n",
" confidence_threshold=0.4,\n",
" input_image_shape=(320, 320),\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "uBhXV5g4Nh42"
},
"outputs": [],
"source": [
"from google.colab import files\n",
"\n",
"files.download(\"yolo_nas_s.onnx\")"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}