# `Monty.Frameworks.Models.Salience.Strategies.Vocus2.Images.ColorSpaceConverter`
[🔗](https://github.com/d-led/ex.tbp.monty/blob/v0.1.0/packages/ex_tbp_monty_core/lib/monty/frameworks/models/salience/strategies/vocus2/images/color_space_converter.ex#L1)

How a salience strategy turns the camera's colour image into the channels it
reasons about.

Mirrors
`tbp/monty/frameworks/models/salience/strategies/vocus2/images.py::ColorSpaceConverter`,
a `Protocol` in Monty, so a strategy can name any function with this shape.
It is a behaviour here: an RGB image in, a float image out, one channel or
several, shifted and scaled so that `[0, 1]` is the whole range.

Monty's three converters — `rgb_to_lab/1`, `rgb_to_opponent/1` and
`rgb_to_opponent_codi/1` — are plain functions in the module beside this one
and are not instances of the protocol; they match its shape, which is all
either needs.

# `rgb`

```elixir
@type rgb() :: [[[float()]]]
```

An RGB image: rows of pixels, each three channels, `0..255` as read.

# `t`

```elixir
@type t() :: struct()
```

# `call`

```elixir
@callback call(t(), rgb()) :: [[[float()]]]
```

The image in the converter's colour space.

---

*Consult [api-reference.md](api-reference.md) for complete listing*