forked from Github/frigate
* Use cosine distance metric for vec tables * Only apply normalization to multi modal searches * Catch possible edge case in stddev calc * Use sigmoid function for normalization for multi modal searches only * Ensure we get model state on initial page load * Only save stats for multi modal searches and only use cosine similarity for image -> image search
This is the Frigate frontend which connects to and provides a User Interface to the Python backend.
Web Development
Installing Web Dependencies Via NPM
Within /web, run:
npm install
Running development frontend
Within /web, run:
PROXY_HOST=<ip_address:port> npm run dev
The Proxy Host can point to your existing Frigate instance. Otherwise defaults to localhost:5000 if running Frigate on the same machine.
Extensions
Install these IDE extensions for an improved development experience:
- eslint