cocomltools 0.1.8

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COCO ML Toolbox

COCO ML Toolbox is a command-line interface (CLI) tool for managing COCO (Common Objects in Context) dataset files. This toolbox provides functionalities to split, merge, and crop COCO datasets, making it easier to manipulate and prepare datasets for machine learning tasks.

Features

• Split a COCO dataset into training and testing datasets with a specified ratio.
• Merge multiple COCO dataset files into a single file.
• Crop images based on annotations in a COCO dataset.

Streamlit App

You can use our streamlit app here.

Installation

cocomltools requires python >= 3.9.8

Install python package

The easiest way to install the package is using pip

pip install cocomltools

You can also clone the source code and install dependencies using poetry:

git clone https://github.com/Ghallabi/coco-ml-toolbox.git
cd coco-ml-toolbox
pip install poetry
poetry install

Usage

We provide a CLI that comes with three main commands: split, merge, and crop. Below are the details on how to use each command.

Split

Splits a COCO dataset into training and testing datasets.

cocoml split --coco-path /path/to/coco.json --output-dir /path/to/output --ratio 0.2 --mode random

• --coco-path: Path to the COCO file (JSON).
• --output-dir: (Optional) Path to save the split COCO files. Defaults to the directory of the input COCO file.
• --ratio: (Optional) Split ratio. Defaults to 0.2.
• --mode: (Optional) Split mode. Options are random and strat. Defaults to random.

Merge

Merges multiple COCO dataset files into a single file.

cocoml merge --coco-paths /path/to/coco1.json,/path/to/coco2.json --output-dir /path/to/output

• --coco-paths: Comma-separated paths to the COCO files (JSON).
• --output-dir: (Optional) Path to save the merged COCO file. Defaults to the directory of the first input COCO file.

Crop

Crops images based on annotations in a COCO dataset.

cocoml crop --coco-path /path/to/coco.json --images-dir /path/to/images --output-dir /path/to/cropped_images --num-workers MAX_WORKERS

• --coco-path: Path to the COCO file (JSON).
• --images-dir: Path to the directory containing the COCO image files.
• --output-dir: (Optional) Path to save the cropped images. Defaults to a "cropped" directory within the parent directory of the images.
• --num-workers: to speed up the cropping process.