Data Conversion Toolkit (CSV, YOLO TXT, Pascal VOC XML)

Installation

pip install -r requirements.txt

Supported Formats

• CSV: filename, width, height, class, xmin, ymin, xmax, ymax
• YOLO TXT: one .txt per image with normalized rows: class_id x_center y_center width height
• Pascal VOC XML: annotation/object/bndbox structure

Commands

• Convert CSV to YOLO TXT

python3 csv_to_txt.py -i annotations.csv -o yolo_txt_output

• Convert CSV to Pascal VOC XML

python3 csv_to_xml.py -i annotations.csv -o voc_xml_output

• Convert YOLO TXT to CSV

python3 txt_to_csv.py -i txt_dir -img images_dir -o annotations.csv --classes classes.json --image-ext .jpg

• Convert YOLO TXT to Pascal VOC XML

python3 txt_to_xml.py -i txt_dir -img images_dir -o voc_xml_output --classes classes.json --image-ext .jpg

• Convert Pascal VOC XML to CSV

python3 xml_to_csv.py -i xml_dir -o annotations.csv

Class Mappings

• When reading YOLO TXT, you may pass --classes with a JSON mapping such as { "0": "person", "1": "car" }.
• When writing YOLO TXT, class names are enumerated to integer identifiers starting from zero.

Architecture

• conversion/models.py: data models ImageAnnotation, ObjectAnnotation, BoundingBox, ImageSize
• conversion/protocols.py: interfaces AnnotationReader, AnnotationWriter
• conversion/readers_*.py: readers for CSV, YOLO TXT, Pascal VOC XML
• conversion/writers_*.py: writers for CSV, YOLO TXT, Pascal VOC XML

Each CLI tool composes readers and writers. The design follows single responsibility, clear dependencies, and extensibility principles.