📦 Object detection with 2D Bounding Box (YOLO)

This project provides a complete pipeline to convert annotation data in JSON format into the YOLO format for object detection tasks. It automatically processes training, validation, and test datasets, creates train.txt and valid.txt image lists, and generates a custom_dataset.yaml configuration file for YOLO training.

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📁 Directory Structure Example

2D_Bounding_Box/
├── training/
│   ├── images/
│   └── labels/         # JSON label files
├── validation/
│   ├── images/
│   └── labels/
├── test/
│   ├── images/
│   └── labels/

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✅ Main Features

📄 1. Image Path List Generation

• Uses glob to collect training and validation image file paths
• Saves them as train.txt and valid.txt for YOLO training

🔄 2. JSON ➝ YOLO Format Conversion

• Extracts Label and Coordinate info from JSON files
• Converts each annotation to YOLO format:

YOLO Format: <class_id> <x_center> <y_center> <width> <height>

• Saves converted annotations to .txt files

🧭 3. Class Mapping and YAML Configuration File Creation

• Generates custom_dataset.yaml with class names and paths to image lists

nc: 9
names: ["car", "truck", "bus", "special_vehicle", "motorcycle", "bicycle", "pedestrian", "traffic_sign", "traffic_light"]
train: path_to_train.txt
val: path_to_valid.txt

📊 4. Data Augmentation using Albumentations

• Horizontal and vertical flips are applied for data augmentation using Albumentations

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🔧 Requirements

• Python 3.8+
• PyTorch
• Albumentations
• TorchVision
• PyYAML

pip install torch torchvision albumentations pyyaml

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📌 Class Mapping

Class ID	Class Name
0	car
1	truck
2	bus
3	special vehicle
4	motorcycle
5	bicycle
6	pedestrian
7	traffic_sign
8	traffic_light

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🗂️ Output Files

File	Description
train.txt, valid.txt	Lists of image file paths
custom_dataset.yaml	YOLO configuration file
.txt (YOLO labels)	Annotation files in YOLO format

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🚀 Future Enhancements

• Add bounding box visualization tool
• Add label validation utilities (e.g., invalid box checker)
• Automate training script generation for YOLOv5/YOLOv8

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📝 References

• Albumentations Documentation
• YOLO Format Guide - Ultralytics