I’ve now managed to get the stream of my HiWatch Series, model HWI- T641H-Z 2.8-12 mm by accessing via browser to rtsp://USERNAME:PASSWORD@192.168.30.50:554/Streaming/Channels/101. Working nice. But on its own, very unusful unless I get storage and image detection going. So, I need something like Frigate.
I believe the Frigate docs suggest running in a docker container installed on a VM. Very convienient as I have Proxmox (installed on a optiples 7070 micropc with 32MB ram) running a VM on which i have a few containers. The idea is to mount a “frigate” dataset created on my Truenas server on Proxmox which is then mounted to the VM. Lots of layers but hoping it should be ok.
I heard that the Google Coral TPU is not sold anymore. Is this going to be a problem for Frigate image recognition? Are there alternatives to the Coral TPU?
You can still get the Google Coral (both the USB dongle and M.2/PCIe versions), but Google has effectively abandoned the official drivers. You’ll need to use community-maintained DKMS drivers if you go with the PCIe version on newer Linux kernels.
If you want a modern alternative, look into the Hailo-8 or Hailo-8L M.2 AI accelerators. They plug right into an open M.2 slot and natively integrate into recent versions of Frigate. Keep in mind that these accelerators ONLY process object detection inference - they do not handle video decoding.
For video decoding, your OptiPlex 7070’s Intel CPU has Quick Sync Video (QSV). You can pass
/dev/drithrough to your container, and Intel iGPU hardware acceleration will handle decoding the RTSP streams with minimal CPU overhead.If you prefer an all-in-one approach, an Intel or Nvidia GPU can handle both video decoding and object detection (via OpenVINO or TensorRT), but a Micro PC limits your physical expansion options.
Storing recordings on a TrueNAS share over NFS or SMB works just fine. Mount the NFS share directly in Proxmox or the VM host, then pass the directory through to your Docker container.