This is an application that displays data saved from an object detection model using Edge Impulse on Raspberry Pi. The project is described in more detail at coffee-cup-detect-runner. The data is retrieved from Supabase.
To get data to the database, you need a Supabase project. It should be already configured following the coffee-cup-detect-runner project. If you didn't do so, check out the project, or follow the following instructions.
You can head over to database.new to create a new Supabase project. When your project is up and running, navigate to the project's SQL Editor and paste in the following snippet:
create table detections (
id uuid NOT NULL DEFAULT uuid_generate_v4(),
created_at timestamp with time zone not null default current_timestamp,
message text
);
This will create a detections table in which you can insert rows every time, for example, a coffee cup is detected.
Alternatively, you can manually navigate to your project's Table Editor and configure the table manually.
Create an .env file (see .env.example) and copy the Supabase credentials, more details here
SUPABASE_URL=<SUPABASE_URL>
SUPABASE_ANON_KEY=<SUPABASE_ANON_KEY>
Then, run the development server:
npm run devOpen http://localhost:3000 with your browser to see the result.
To learn more about Next.js, take a look at the following resources:
- https://nextjs.org/docs - learn about Next.js features and API.
- https://nextjs.org/learn - an interactive Next.js tutorial.
To learn about the entire project, go to coffee-cup-detect-runner. To learn about Edge Impulse follow these resources:
- https://docs.edgeimpulse.com/docs/raspberry-pi-4
- https://docs.edgeimpulse.com/docs/tutorials/end-to-end-tutorials/object-detection/object-detection
To learn about Supabase, take a look at the following resources: