Picolo

A very simple Image-reading crate for plotting data and transposing image contents into a detailed data structure with the precision decided by the user.

Precision explanation: Say you only wanted to count every 10 pixels to increase performance, and your AI model doesn't care about individual pixels. Changing the pixel from 1 to 10 will do that, and allow you to compute more data for your buck.

Basic plot

```rust

// Plotting a 2d Vector // @Params: x: &u32, y: &u32 use picolo::plot::plot_tbl; fn main() { let x = vec![0, 152, 142, 500, 50, 169]; let y = vec![0, 152, 100, 600, 50, 152]; plot(&x, &y); } ```

Setting up image transpose

```rust

// Easiest way to print half the contents let pixlstruct = loadpicture("images/icon.png", 2);

for i in pixl_struct { println!("{:?}", i); }

// Accessing all fields: // @Params: &path as &str, precision as u32 (1 = 100% precision, 2 = 50%, ...)
use picolo::readimg::load_picture;

let foo = "images/icon.png"; let barstr = &foo; let precision = 1; let pixlstruct = picolo::loadpicture(barstr, precision);

// Print all the contents derived from image for i in pixl_struct { println!("x {} y {} red {} green {} blue: {}", i[0].x, i[0].y, i[0].color.red, i[0].color.green, i[0].color.blue); }

```

TODO:

• Add option to draw circles if preferred (.json file preferably)
• Add coloring variation if dataset become too large for the plot
• Add text above individual datapoints (Display: as '50, 12')
• Add line drawing
• Add function to open image after the plot has been drawn so the user doesn't have to
• Refactor current way of finding origin with more exact positions