Vehicle Detection System using Yolov9

Excited to share our project on Vehicle Type Detection using YOLOv9n :red_car::motorcycle::bus:
Engineered a real-time Vehicle Type Detection system using YOLOv9n, custom datasets from Roboflow, and Python-based AI workflows accelerated with NVIDIA GPU computing.

The model was trained to accurately detect and classify multiple vehicle categories, including:
Cars
Motorcycle
Buses
Trucks
Bicycle

The dataset was carefully structured using diverse traffic conditions, multiple road environments, varying lighting scenarios, camera perspectives, object distances, and real-world street data to improve model robustness and detection consistency.

Key Areas Worked On:

Computer Vision Engineering
Object Detection Architectures
Dataset Collection & Annotation
Deep Learning Workflows
Real-Time Inference Systems
GPU-Accelerated Model Training
Detection Accuracy Optimization
Performance Tuning & Validation
Intelligent Traffic Monitoring Solutions

Worked extensively on improving confidence scores, minimizing false detections, and enhancing detection performance under dynamic environmental conditions such as:
Low-light environments
Traffic congestion
Different weather and visibility conditions
Varying vehicle distances and camera angles

This project provided practical exposure to the complete AI development lifecycle from dataset preparation and preprocessing to training, testing, optimization, and deployment-oriented experimentation.
Beyond technical implementation, the experience strengthened my understanding of scalable AI-powered vision systems designed for intelligent transportation, autonomous infrastructure, and real-world automation applications.

Team members : Ayush Kini, Tanaya Bagade, Ricky Patel, Satyam Mahto.

Special thanks to our trainers:
chandani Yadav, Nidhi Thakur, and Aditya Behera

Under the guidance of:
Sandeep Dwivedi, Dr. Sunny Sall and Romero D’Souza

In collaboration with:
Dr. Chandrakant Bothe
YOLOvX

Continuously exploring domains like Artificial Intelligence, Computer Vision, Deep Learning, Intelligent Systems, and Autonomous Technologies.

#AI #ComputerVision #DeepLearning #YOLO #YOLOv9 #ObjectDetection #Python #MachineLearning #VehicleDetection #VehicleTypeDetection #NVIDIA #Roboflow #ArtificialIntelligence #OpenCV #Automation #IntelligentSystems #TechProjects #LearningByDoing