So I’ve been self-hosting my CCTV for about 3 years now and it’s always been… not great
First I gave Blue Iris a try which meant I needed a full Windows VM to run it
And it worked - it did the job and recorded stuff and it was fairly OK at motion detection, but damn did it eat the CPU and draw a lot of electricity for no real reason
A few months later I gave Shinobi CCTV a try in Docker and that’s what I’ve been running since
Again, it’s mostly fine but the UI is a little clunky and my use case of “24/7 recording that I can easily watch back” was mostly being met, although I had 1 problem
By default Shinobi segments video into 15 minute chunks
So if someone smashes into my car at 14:45:01 then I can’t watch that footage until 15:00
Obviously this is a big flaw, so to get around this I changed the segment size to 1 minute
But I have 4 cameras, so this means that over a day I’ll now have 5760 clips per day
Sifting through those to find some footage is not fun
Enter Frigate - I’d tried it before but never really gave it a full chance
It’s a bit to wrap your head around at first, but once it’s up and running it’s just a docker-compose.yml for the container and a simple frigate.yml config file
The docs are EXTENSIVE and answered almost every question I had
But there’s 1 extra awesome feature I wasn’t originally aware of: OpenVINO
OpenVINO is a deep learning model from Intel that apparently runs on my old Broadwell gen Xeon E5-2650v4 CPUs without issue
I’ve turned it on and enabled object detection and I gotta say, WOW, it’s very good
I can go outside with the dog, walk around for a moment and come back in and it’ll pick both of us up no problem
So this saved me about £100 seeing as I don’t need a Coral compute module (OK I could still get one, but I’m happy for now)
And just to top all of this off, Frigate and Reolink cameras generally don’t play too nicely together, yet with support from the docs, mine are working great
Looking at Zabbix, my CPU utilisation for my CCTV server was averaging 10% whilst using Shinobi
Now it’s up to 50% but my UPS runtime hasn’t really changed so I’m calling that a win
My config is below if it helps anyone trying to get this set up with Reolink cameras
# Disable MQTT because I'm not connecting this to Home Assistant
mqtt:
enabled: false
# Enable 24/7 recording (mode: all means all clips, not just clips with objects in)
# Keep 30 days worth of footage (Frigate automatically deletes the oldest footage once space gets extremely low)
record:
enabled: true
retain:
days: 30
mode: all
# Set the birdseye view to always show a live stream of the cameras
birdseye:
mode: continuous
# Detection area for cameras (all 4 of my Reolink RLC-410 cameras are 2560x1920)
detect:
width: 2560
height: 1920
# Objects to track from /labelmap.txt
objects:
track:
- person
- bicycle
- car
- motorcycle
- bird
- cat
- dog
# Copy and paste from docs to use default OpenVINO
# https://docs.frigate.video/configuration/detectors/#openvino-detector
detectors:
ov:
type: openvino
device: AUTO
model:
path: /openvino-model/ssdlite_mobilenet_v2.xml
model:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
labelmap_path: /openvino-model/coco_91cl_bkgr.txt
# Config for each camera
cameras:
c1-side:
ffmpeg:
inputs:
# Record HD stream
- path: http://10.10.8.11/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password={FRIGATE_C1_PASS}
input_args: preset-http-reolink
roles:
- record
# Use low quality and low FPS stream for object detection
- path: http://10.10.8.11/flv?port=1935&app=bcs&stream=channel0_sub.bcs&user=admin&password={FRIGATE_C1_PASS}
input_args: preset-http-reolink
roles:
- detect
# Record audio
output_args:
record: preset-record-generic-audio-copy
c2-garden:
ffmpeg:
inputs:
- path: http://10.10.8.12/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password={FRIGATE_C2_PASS}
input_args: preset-http-reolink
roles:
- record
- path: http://10.10.8.12/flv?port=1935&app=bcs&stream=channel0_sub.bcs&user=admin&password={FRIGATE_C2_PASS}
input_args: preset-http-reolink
roles:
- detect
output_args:
record: preset-record-generic-audio-copy
c3-garage:
ffmpeg:
inputs:
- path: http://10.10.8.13/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password={FRIGATE_C3_PASS}
input_args: preset-http-reolink
roles:
- record
- path: http://10.10.8.13/flv?port=1935&app=bcs&stream=channel0_sub.bcs&user=admin&password={FRIGATE_C3_PASS}
input_args: preset-http-reolink
roles:
- detect
output_args:
record: preset-record-generic-audio-copy
c4-front:
ffmpeg:
inputs:
- path: http://10.10.8.14/flv?port=1935&app=bcs&stream=channel0_main.bcs&user=admin&password={FRIGATE_C4_PASS}
input_args: preset-http-reolink
roles:
- record
- path: http://10.10.8.14/flv?port=1935&app=bcs&stream=channel0_sub.bcs&user=admin&password={FRIGATE_C4_PASS}
input_args: preset-http-reolink
roles:
- detect
output_args:
record: preset-record-generic-audio-copy
One thing to mention is that you’re currently running detection on 2560x1920 but your reolink ext stream is going to be something like 896x672 so you’re using cpu to scale that stream up to the higher resolution. You may find lower cpu usage by running detect at that streams specific resolution