Crate cocotools 

The cocotools crate provides tools to load, manipulate, convert and visualize COCO format datasets. The base class is the COCO struct, usually loaded from a COCO json annotation file.

This crate aims to provide similar functionalities to the python pycocotools package / cocoapi with additionnal utilities such as conversion between dataset formats. It also aims to have a better documentation and a more readable implementation.

Usage examples

Getting information about an image..

use cocotools::COCO;

let annotations_file_path = PathBuf::from("../data_samples/coco_25k/annotations.json");
let image_folder_path = PathBuf::from("../data_samples/coco_25k/images");
let coco_dataset = COCO::new(&annotations_file_path, &image_folder_path)?;
assert_eq!(coco_dataset.get_img(17627)?.file_name, "000000017627.jpg");

Loading a segmentation mask

use cocotools::COCO;
use cocotools::mask;
use cocotools::mask::conversions;
use cocotools::coco::object_detection;

let annotations_file_path = PathBuf::from("../data_samples/coco_25k/annotations.json");
let image_folder_path = PathBuf::from("../data_samples/coco_25k/images");
let coco_dataset = COCO::new(&annotations_file_path, &image_folder_path)?;
let anns = coco_dataset.get_img_anns(174482)?;
let mask = mask::Mask::try_from(&anns[0].segmentation)?;
assert_eq!(mask.ncols(), 388);
assert_eq!(mask.nrows(), 640);

Re-exports

pub use crate::coco::COCO;

Modules

coco

Module containing the data annotation formats.

errors

Module with the errors for the crate.

mask

Module containing utilities to convert data formats.

visualize

Module for drawing and displaying annotations.