verifyannotations 0.1

verify YOLO data annotations

VerifyDataAnnotations

Overview

VerifyDataAnnotations is a Python package specifically designed to validate and annotate image data with bounding boxes using annotations provided in YOLO format text files. It serves as a tool for verifying the correctness of annotations and ensuring the integrity of datasets intended for use in computer vision tasks, especially those utilizing the YOLO object detection framework.

Features

• Validates the structure of image and label directories.
• Checks if label files contain valid annotations in YOLO format.
• Ensures that image files have the correct format.
• Annotates images with bounding boxes based on YOLO label annotations.
• Saves annotated images to an output directory.

Input Parameters

• label_folder: Path to the directory containing label files with annotations in YOLO format.
• raw_image_folder: Path to the directory containing the raw image files.
• output_image_folder: Path to the directory where annotated images will be saved.
• image_name_list_path: Path to the text file listing the names of all images in the dataset.
• class_path: Path to the text file containing the list of classes or labels used in the dataset.

Installation

You can install VerifyDataAnnotations via pip:

pip install verifyannotations

Example

Suppose we have the following directory structure:

dataset/
│
├── labels/
│   ├── image1.txt
│   ├── image2.txt
│   └── ...
│
├── images/
│   ├── image1.bmp
│   ├── image2.bmp
│   └── ...
│
├── saved_annotations/
│
├── name_list.txt
└── classes.txt

The labels directory contains text files with annotation data in YOLO format. The images directory contains corresponding image files. saved_annotations will store the annotated images.

Using VerifyDataAnnotations:

from verifyannotations import VerifyDataAnnotations

label_folder = "dataset/labels"
raw_image_folder = "dataset/images"
output_image_folder = "dataset/saved_annotations"
image_name_list_path = "dataset/name_list.txt"
class_path = "dataset/classes.txt"

verifier = VerifyDataAnnotations(
    label_folder,
    raw_image_folder,
    output_image_folder,
    image_name_list_path,
    class_path,
)

verifier.verify_annotations()

This will validate the annotations, annotate the images with bounding boxes, and save the annotated images to the saved_annotations directory.