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https://github.com/blakeblackshear/frigate.git
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Update deps (#19617)
* Update virtualenv * Fix device ID * Fix dependency conflict * Cleanup mypy
This commit is contained in:
Nicolas Mowen
GitHub
parent
8e254aa1f0
commit
e92267d7e2
@ -1,22 +1,23 @@
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aiofiles == 24.1.*
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click == 8.1.*
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# FastAPI
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aiohttp == 3.11.3
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starlette == 0.41.2
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starlette-context == 0.3.6
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fastapi == 0.115.*
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uvicorn == 0.30.*
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aiohttp == 3.12.*
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starlette == 0.47.*
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starlette-context == 0.4.*
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fastapi[standard-no-fastapi-cloud-cli] == 0.116.*
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uvicorn == 0.35.*
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slowapi == 0.1.*
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joserfc == 1.0.*
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pathvalidate == 3.2.*
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joserfc == 1.2.*
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cryptography == 44.0.*
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pathvalidate == 3.3.*
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markupsafe == 3.0.*
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python-multipart == 0.0.12
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python-multipart == 0.0.20
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# Classification Model Training
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tensorflow == 2.19.* ; platform_machine == 'aarch64'
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tensorflow-cpu == 2.19.* ; platform_machine == 'x86_64'
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# General
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mypy == 1.6.1
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onvif-zeep-async == 3.1.*
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onvif-zeep-async == 4.0.*
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paho-mqtt == 2.1.*
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pandas == 2.2.*
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peewee == 3.17.*
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@ -30,7 +31,7 @@ ruamel.yaml == 0.18.*
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tzlocal == 5.2
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requests == 2.32.*
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types-requests == 2.32.*
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norfair == 2.2.*
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norfair == 2.3.*
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setproctitle == 1.3.*
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ws4py == 0.5.*
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unidecode == 1.3.*
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@ -5,15 +5,10 @@ from typing import Any, Sequence
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import cv2
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import numpy as np
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from norfair import (
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Detection,
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Drawable,
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OptimizedKalmanFilterFactory,
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Tracker,
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draw_boxes,
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)
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from norfair.drawing.drawer import Drawer
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from norfair.tracker import TrackedObject
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from norfair.drawing.draw_boxes import draw_boxes
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from norfair.drawing.drawer import Drawable, Drawer
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from norfair.filter import OptimizedKalmanFilterFactory
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from norfair.tracker import Detection, TrackedObject, Tracker
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from rich import print
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from rich.console import Console
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from rich.table import Table
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@ -198,19 +193,21 @@ class NorfairTracker(ObjectTracker):
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self.default_tracker = {
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"static": Tracker(
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distance_function=frigate_distance,
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distance_threshold=self.default_tracker_config["distance_threshold"],
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distance_threshold=self.default_tracker_config[ # type: ignore[arg-type]
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"distance_threshold"
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],
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initialization_delay=self.detect_config.min_initialized,
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hit_counter_max=self.detect_config.max_disappeared,
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filter_factory=self.default_tracker_config["filter_factory"],
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hit_counter_max=self.detect_config.max_disappeared, # type: ignore[arg-type]
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filter_factory=self.default_tracker_config["filter_factory"], # type: ignore[arg-type]
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),
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"ptz": Tracker(
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distance_function=frigate_distance,
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distance_threshold=self.default_ptz_tracker_config[
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"distance_threshold"
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],
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], # type: ignore[arg-type]
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initialization_delay=self.detect_config.min_initialized,
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hit_counter_max=self.detect_config.max_disappeared,
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filter_factory=self.default_ptz_tracker_config["filter_factory"],
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hit_counter_max=self.detect_config.max_disappeared, # type: ignore[arg-type]
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filter_factory=self.default_ptz_tracker_config["filter_factory"], # type: ignore[arg-type]
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),
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}
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@ -273,7 +270,7 @@ class NorfairTracker(ObjectTracker):
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# Get the correct tracker for this object's label
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tracker = self.get_tracker(obj["label"])
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obj_match = next(
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(o for o in tracker.tracked_objects if o.global_id == track_id), None
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(o for o in tracker.tracked_objects if str(o.global_id) == track_id), None
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)
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# if we don't have a match, we have a new object
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obj["score_history"] = (
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@ -317,7 +314,7 @@ class NorfairTracker(ObjectTracker):
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tracker.tracked_objects = [
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o
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for o in tracker.tracked_objects
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if o.global_id != track_id and o.hit_counter < 0
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if str(o.global_id) != track_id and o.hit_counter < 0
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]
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del self.track_id_map[track_id]
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@ -565,12 +562,12 @@ class NorfairTracker(ObjectTracker):
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"estimate": estimate,
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"estimate_velocity": t.estimate_velocity,
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}
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active_ids.append(t.global_id)
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if t.global_id not in self.track_id_map:
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self.register(t.global_id, new_obj)
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active_ids.append(str(t.global_id))
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if str(t.global_id) not in self.track_id_map:
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self.register(str(t.global_id), new_obj)
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# if there wasn't a detection in this frame, increment disappeared
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elif t.last_detection.data["frame_time"] != frame_time:
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id = self.track_id_map[t.global_id]
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id = self.track_id_map[str(t.global_id)]
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self.disappeared[id] += 1
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# sometimes the estimate gets way off
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# only update if the upper left corner is actually upper left
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@ -578,7 +575,7 @@ class NorfairTracker(ObjectTracker):
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self.tracked_objects[id]["estimate"] = new_obj["estimate"]
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# else update it
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else:
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self.update(t.global_id, new_obj)
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self.update(str(t.global_id), new_obj)
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# clear expired tracks
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expired_ids = [k for k in self.track_id_map.keys() if k not in active_ids]
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@ -613,7 +610,7 @@ class NorfairTracker(ObjectTracker):
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def debug_draw(self, frame: np.ndarray, frame_time: float) -> None:
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# Collect all tracked objects from each tracker
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all_tracked_objects = []
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all_tracked_objects: list[TrackedObject] = []
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# print a table to the console with norfair tracked object info
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if False:
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@ -644,9 +641,9 @@ class NorfairTracker(ObjectTracker):
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# draw the estimated bounding box
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draw_boxes(frame, all_tracked_objects, color="green", draw_ids=True)
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# draw the detections that were detected in the current frame
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draw_boxes(frame, active_detections, color="blue", draw_ids=True)
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draw_boxes(frame, active_detections, color="blue", draw_ids=True) # type: ignore[arg-type]
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# draw the detections that are missing in the current frame
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draw_boxes(frame, missing_detections, color="red", draw_ids=True)
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draw_boxes(frame, missing_detections, color="red", draw_ids=True) # type: ignore[arg-type]
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# draw the distance calculation for the last detection
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# estimate vs detection
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@ -654,8 +651,8 @@ class NorfairTracker(ObjectTracker):
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ld = obj.last_detection
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# bottom right
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text_anchor = (
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ld.points[1, 0],
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ld.points[1, 1],
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ld.points[1, 0], # type: ignore[index]
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ld.points[1, 1], # type: ignore[index]
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)
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frame = Drawer.text(
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frame,
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@ -284,7 +284,7 @@ def post_process_yolox(
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def get_ort_providers(
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force_cpu: bool = False, device: str = "AUTO", requires_fp16: bool = False
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force_cpu: bool = False, device: str | None = "AUTO", requires_fp16: bool = False
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) -> tuple[list[str], list[dict[str, Any]]]:
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if force_cpu:
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return (
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@ -301,7 +301,7 @@ def get_ort_providers(
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for provider in ort.get_available_providers():
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if provider == "CUDAExecutionProvider":
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device_id = 0 if not device.isdigit() else int(device)
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device_id = 0 if (not device or not device.isdigit()) else int(device)
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providers.append(provider)
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options.append(
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{
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