[frigate] frigate v4.0.0-beta (#135)

* frigate v4.0.0-beta

* fixing linting errors
This commit is contained in:
Jeff Billimek 2020-01-15 23:31:44 -05:00 committed by GitHub
parent 6fe7be4d7e
commit 406628ef0a
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3 changed files with 101 additions and 31 deletions

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@ -1,8 +1,8 @@
apiVersion: v1 apiVersion: v1
appVersion: "0.2.0" appVersion: "0.4.0"
description: Realtime object detection on RTSP cameras with the Google Coral description: Realtime object detection on RTSP cameras with the Google Coral
name: frigate name: frigate
version: 1.0.0 version: 2.0.0
keywords: keywords:
- tensorflow - tensorflow
- coral - coral

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@ -39,14 +39,18 @@ spec:
containerPort: 5000 containerPort: 5000
protocol: TCP protocol: TCP
livenessProbe: livenessProbe:
tcpSocket: httpGet:
path: /
port: http port: http
scheme: HTTP
initialDelaySeconds: 30 initialDelaySeconds: 30
failureThreshold: 5 failureThreshold: 5
timeoutSeconds: 5 timeoutSeconds: 5
readinessProbe: readinessProbe:
tcpSocket: httpGet:
path: /
port: http port: http
scheme: HTTP
initialDelaySeconds: 30 initialDelaySeconds: 30
failureThreshold: 5 failureThreshold: 5
timeoutSeconds: 5 timeoutSeconds: 5
@ -55,7 +59,7 @@ spec:
- name: TZ - name: TZ
value: "{{ .Values.timezone }}" value: "{{ .Values.timezone }}"
{{- end }} {{- end }}
- name: RTSP_PASSWORD - name: FRIGATE_RTSP_PASSWORD
value: "{{ .Values.rtspPassword }}" value: "{{ .Values.rtspPassword }}"
volumeMounts: volumeMounts:
- mountPath: /dev/bus/usb - mountPath: /dev/bus/usb

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@ -9,7 +9,7 @@ strategyType: Recreate
image: image:
repository: blakeblackshear/frigate repository: blakeblackshear/frigate
tag: 0.2.0 tag: 0.4.0-beta
pullPolicy: IfNotPresent pullPolicy: IfNotPresent
rtspPassword: password rtspPassword: password
@ -20,21 +20,89 @@ fullnameOverride: ""
# frigate configuration - see https://github.com/blakeblackshear/frigate/blob/master/config/config.yml for example # frigate configuration - see https://github.com/blakeblackshear/frigate/blob/master/config/config.yml for example
config: | config: |
web_port: 5000
mqtt: mqtt:
host: mqtt.server.com host: mqtt.server.com
topic_prefix: frigate topic_prefix: frigate
# client_id: frigate # Optional -- set to override default client id of 'frigate' if running multiple instances
# user: username # Optional -- Uncomment for use # user: username # Optional -- Uncomment for use
# password: password # Optional -- Uncomment for use # password: password # Optional -- Uncomment for use
#################
# Default ffmpeg args. Optional and can be overwritten per camera.
# Should work with most RTSP cameras that send h264 video
# Built from the properties below with:
# "ffmpeg" + global_args + input_args + "-i" + input + output_args
#################
# ffmpeg:
# global_args:
# - -hide_banner
# - -loglevel
# - panic
# hwaccel_args: []
# input_args:
# - -avoid_negative_ts
# - make_zero
# - -fflags
# - nobuffer
# - -flags
# - low_delay
# - -strict
# - experimental
# - -fflags
# - +genpts+discardcorrupt
# - -vsync
# - drop
# - -rtsp_transport
# - tcp
# - -stimeout
# - '5000000'
# - -use_wallclock_as_timestamps
# - '1'
# output_args:
# - -vf
# - mpdecimate
# - -f
# - rawvideo
# - -pix_fmt
# - rgb24
####################
# Global object configuration. Applies to all cameras
# unless overridden at the camera levels.
# Keys must be valid labels. By default, the model uses coco (https://dl.google.com/coral/canned_models/coco_labels.txt).
# All labels from the model are reported over MQTT. These values are used to filter out false positives.
# min_area (optional): minimum width*height of the bounding box for the detected person
# max_area (optional): maximum width*height of the bounding box for the detected person
# threshold (optional): The minimum decimal percentage (50% hit = 0.5) for the confidence from tensorflow
####################
objects:
track:
- person
- car
- truck
filters:
person:
min_area: 5000
max_area: 100000
threshold: 0.5
cameras: cameras:
back: back:
rtsp: ffmpeg:
user: viewer ################
host: 10.0.10.10 # Source passed to ffmpeg after the -i parameter. Supports anything compatible with OpenCV and FFmpeg.
port: 554 # Environment variables that begin with 'FRIGATE_' may be referenced in {}
# values that begin with a "$" will be replaced with environment variable ################
password: $RTSP_PASSWORD input: rtsp://viewer:{FRIGATE_RTSP_PASSWORD}@10.0.10.10:554/cam/realmonitor?channel=1&subtype=2
path: /cam/realmonitor?channel=1&subtype=2 #################
# These values will override default values for just this camera
#################
# global_args: []
# hwaccel_args: []
# input_args: []
# output_args: []
################ ################
## Optional mask. Must be the same dimensions as your video feed. ## Optional mask. Must be the same dimensions as your video feed.
@ -54,36 +122,34 @@ config: |
take_frame: 1 take_frame: 1
################ ################
# Optional hardware acceleration parameters for ffmpeg. If your hardware supports it, it can # Overrides for global object config
# greatly reduce the CPU power used to decode the video stream. You will need to determine which
# parameters work for your specific hardware. These may work for those with Intel hardware that
# supports QuickSync.
################ ################
# ffmpeg_hwaccel_args: objects:
# - -hwaccel track:
# - vaapi - person
# - -hwaccel_device filters:
# - /dev/dri/renderD128 person:
# - -hwaccel_output_format min_area: 5000
# - yuv420p max_area: 100000
threshold: 0.5
################
# size: size of the region in pixels
# x_offset/y_offset: position of the upper left corner of your region (top left of image is 0,0)
# Tips: All regions are resized to 300x300 before detection because the model is trained on that size.
# Resizing regions takes CPU power. Ideally, all regions should be as close to 300x300 as possible.
# Defining a region that goes outside the bounds of the image will result in errors.
################
regions: regions:
- size: 350 - size: 350
x_offset: 0 x_offset: 0
y_offset: 300 y_offset: 300
min_person_area: 5000
threshold: 0.5
- size: 400 - size: 400
x_offset: 350 x_offset: 350
y_offset: 250 y_offset: 250
min_person_area: 2000
threshold: 0.5
- size: 400 - size: 400
x_offset: 750 x_offset: 750
y_offset: 250 y_offset: 250
min_person_area: 2000
threshold: 0.5
service: service:
type: ClusterIP type: ClusterIP
port: 5000 port: 5000