Cars - Overhead View Computer Vision Project

Car Detection Overhead View

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Description

Background Information

This dataset was curated and annotated by Ishaan Singh, a high school student from India.

The original dataset (v1) is composed of 166 images of various cars present in a junkyard. Training Set: 116 images, Validation Set: 33 images, Testing Set: 17 images.

The dataset is available under the Public License.

Ishaan ultimately used this dataset to create a "Drone Surveillance" system to count the cars using YOLOv5 & Deep SORT (Simple Online and Realtime Tracking with a Deep Association Metric) for a contest organized by ComputerVisionZone.

Here is a video of his final submission for the contest: Video of Ishaan's Final Model

Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

Dataset Versions

Version 1 (v1) - 166 images

  • Preprocessing: Auto-Orient and Resize (Stretch to 416x416)
  • Augmentations: No augmentations applied
  • Training Metrics: This version of the dataset was not trained

Use This Trained Model

Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.

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Cite This Project

LICENSE
Public Domain

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

                        @misc{
                            cars---overhead-view_dataset,
                            title = { Cars - Overhead View Dataset },
                            type = { Open Source Dataset },
                            author = { Car Detection Overhead View },
                            howpublished = { \url{ https://universe.roboflow.com/car-detection-overhead-view/cars---overhead-view } },
                            url = { https://universe.roboflow.com/car-detection-overhead-view/cars---overhead-view },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-11-17 },
                            }
                        
                    

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