Digits Object Detection Dataset and Pre-Trained Model by Phils Workspace

Images

841 images

Explore Dataset

Project Overview:

The original goal was to use this model to monitor my rowing workouts and learn more about computer vision. To monitor the workouts, I needed the ability to identify the individual digits on the rowing machine. With the help of Roboflow's computer vision tools, such as assisted labeling, I was able to more quickly prepare, test, deploy and improve my YOLOv5 model. Example Annotated Image from the Dataset

Inference on a Test Image using the rfWidget

How to Use the rfWidget

Roboflow's Upload API, which is suitable for uploading images, video, and annotations, worked great with a custom app I developed to modify the predictions from the deployed model, and export them in a format that could be uploaded to my workspace on Roboflow.

What took me weeks to develop can now be done with the help of a single click utilize Roboflow Train, and the Upload API for Active Learning (dataset and model improvement). Training Results - Roboflow FAST Model

Dataset Classes:

1, 2, 3, 4, 5, 6, 7, 8, 9, 90 (class "90" is a stand-in for the digit, zero)

This dataset consits of 841 images. There are images from a different rowing machine and also from this repo. Some scenes are illuminated with sunlight. Others have been cropped to include only the LCD. Digits like 7, 8, and 9 are underrepresented.

For more information:

A full tutorial for creating and deploying this model with YOLOv5: https://vision.philbrockman.com/

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite this Project

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

@misc{ digits-coi4f_dataset,
    title = { Digits Dataset },
    type = { Open Source Dataset },
    author = { Phils Workspace },
    howpublished = { \url{ https://universe.roboflow.com/phils-workspace/digits-coi4f } },
    url = { https://universe.roboflow.com/phils-workspace/digits-coi4f },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { aug },
    note = { visited on 2023-12-01 },
}