Slideshow https://docs.google.com/presentation/d/1UTmFRhRUZX39BidE1qS52Vgtm6KRH3L51piaHyVcK8c/edit?usp=sharing

Darwin Viewer

View Darwin's notes! Match Darwin's notes! Basically - be Darwin.

Install

git clone https://github.com/HackTheStacks/darwin-viewer
cd darwin-viewer
npm install

Possible other dependencies:

brew install sqlite3
npm install -g sqlite3
npm install -g sequelize

Usage

sequelize db:migrate
sequelize db:seed:all
npm start

API

GET /api/fragments

Options:

• page: Paginated data

Response:

• JSON

[
	{
		"id": "1",
		"url": "/fragments/1/image",
	}
	...
]

GET /api/fragments/:id

Params:

• id: Fragment id.

Response:

• JSON
• Matches where baseId is id

{
	"id": "1",
	"text": "Text content...",
	"url": "/fragments/1/image",
	"matches": [
		{
            "id": 10,
			"baseId": 1,
            "targetId": 2,
			"edge": "S",
			"confidence": 0.9,
			"votes": 3
		}
		...
	]
}

GET /api/fragments/:id/image

Params:

• id: Fragment id.

Response:

• Image File (jpg/png)

POST /api/matches

Body:

• baseId: Id of main fragment.
• targetId: Second fragment matched against.
• edge: Relative to main fragment. (N, S, E, W)
• confidence: Number to indicate the confidence of the match.

{
    "baseId": 2,
	"targetId": 1,
	"edge": "S",
	"confidence": 9,
    "votes": 10,
}

PUT /api/matches/:id/(upvote | downvote)

Params:

• id: Id of a match to upvote / downvote

What we need

The api pulls all of it's data from an sqlite3 database. Some options for getting the datas into this database.

We don't need all the data. 20 images that have some relations would be totally fine for demo purposes.

1) Populate an sqlite database yourself!

You can take a look at the files in /migrations to see the sqlite3 schema. You would need a row for every slice picture (called fragments) and another row for all matches for a given fragment.

Might be annoying replicating a database though ¯\_(ツ)_/¯.

2) Populate a .csv file!

Fill out a .csv file with whatever you want. Perhaps 2 files:

• 1 containing information about fragment files (ids, filenames)
• 1 containing relations for fragments (baseFragmentId, targetFragmentId ie. some id for a fragment that was compared to base, confidence score for how related they are, edge value describing which base edge the target likely lines up with)

We can then take these CSVs and write a script to populate our sqlite3 database using this information.

3) Provide a tool for comparing images!

Deliver some executable that can accept two images and compare them. We'll take some of the provided data, load it into our database and then call the executable to generate the matches. That should be fun!

4) Create your own API!

I don't quite know why you would do that. But I heard it being spoken after a few bottles of Club-Mate, so I guess it's a thing that's been thought.