Car Models - Stage 1 Computer Vision Project

Tyler

Updated a year ago

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Classes (10)
Chevrolet Silverado
Ford F-Series
Honda CR-V
Honda Civic
Hyundai Elantra
Kia Rio
RAM 1500-2500-3500
Toyota Corrola
Toyota RAV4
Toyota Tacoma

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Description

This project was built for detecting color and car model using two-stage detection and distance between two cars using mathmatical abstraction: https://github.com/Tyler-Odenthal/Car_Distance_Project

Companion Project: https://universe.roboflow.com/tyler-yonjx/car-colors-1smyc/dataset/5

Objectives for the Project

  • Use Object Detection to Determine Car Model

  • Use Classification to Determine Car Color

  • Bonus: Calculate Distance Between Two Cars

By using two stage detection we can combine 10 car model types and 10 car colors to get 100 different detection combinations. Power of Combinations

Potential Use Cases

  • 200 Amber Alerts each Year -> Enhancing DOT Cameras to Help Track Bad Actors

  • 2B+ Parking Spaces in the USA -> Optimize Parking Garages and Enhance User Experience with Consumer Trends

  • 3.2T+ US Miles Driven Each Year -> Monitoring Flow of Traffic and Estimating Accident Risks Profiles Based on Flow and Car Types

Estimate Distance

GitHub code can be modified to calculate distance between any numbers of cars or model type. Current iteration only accounts for Hyundia Elantra and Kia Rio. Will update code to be more robust if there is significant interest.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            car-models-stage-1_dataset,
                            title = { Car Models - Stage 1 Dataset },
                            type = { Open Source Dataset },
                            author = { Tyler },
                            howpublished = { \url{ https://universe.roboflow.com/tyler-yonjx/car-models-stage-1 } },
                            url = { https://universe.roboflow.com/tyler-yonjx/car-models-stage-1 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-11-24 },
                            }
                        
                    

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