Ilyes Talbi

futbol players

Object Detection

futbol players Computer Vision Project

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Images

163 images
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Background Information

This dataset was curated and annotated by Ilyes Talbi, Head of La revue IA, a French publication focused on stories of machine learning applications.

Main objetive is to identify if soccer (futbol) players, the referree and the soccer ball (futbol).

The original custom dataset (v1) is composed of 163 images.

  • Class 0 = players
  • Class 1 = referree
  • Class 2 = soccer ball (or futbol)

The dataset is available under the Public License.

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 7 (v7) - 163 images (raw images)

  • Preprocessing: Auto-Orient, Modify Classes: 3 remapped, 0 dropped
    • Modified Classes: Class 0 = players, Class 1 = referree, Class 2 = futbol
  • Augmentations: No augmentations applied
  • Training Metrics: This version of the dataset was not trained

Version 2 (v2) - 163 images

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

Version 3 (v3) - 391 images

  • Preprocessing: Auto-Orient and Resize (Stretch to 416x416), Modify Classes: 3 remapped, 0 dropped
    • Modified Classes: Class 0 = players, Class 1 = referree, Class 2 = futbol
  • Augmentations:
    • Outputs per training example: 3
    • Rotation: Between -25° and +25°
    • Shear: ±15° Horizontal, ±15° Vertical
    • Brightness: Between -25% and +25%
    • Blur: Up to 0.75px
    • Noise: Up to 1% of pixels
    • Bounding Box: Blur: Up to 0.5px
  • Training Metrics: 86.4%mAP, 51.8% precision, 90.4% recall

Version 4 (v4) - 391 images

  • Preprocessing: Auto-Orient and Resize (Stretch to 416x416), Modify Classes: 3 remapped, 0 dropped
    • Modified Classes: Class 0 = players, Class 1 = referree, Class 2 = futbol
  • Augmentations:
    • Outputs per training example: 3
    • Rotation: Between -25° and +25°
    • Shear: ±15° Horizontal, ±15° Vertical
    • Brightness: Between -25% and +25%
    • Blur: Up to 0.75px
    • Noise: Up to 1% of pixels
    • Bounding Box: Blur: Up to 0.5px
  • Training Metrics: 84.6% mAP, 52.3% precision, 85.3% recall

Version 5 (v5) - 391 images

  • Preprocessing: Auto-Orient and Resize (Stretch to 416x416), Modify Classes: 3 remapped, 2 dropped
    • Modified Classes: Class 0 = players, Class 1 = referree, Class 2 = futbol
      • Only Class 0, which was remapped to players was included in this version
  • Augmentations:
    • Outputs per training example: 3
    • Rotation: Between -25° and +25°
    • Shear: ±15° Horizontal, ±15° Vertical
    • Brightness: Between -25% and +25%
    • Blur: Up to 0.75px
    • Noise: Up to 1% of pixels
    • Bounding Box: Blur: Up to 0.5px
  • Training Metrics: Trained from the COCO Checkpoint in Public Models ("transfer learning") on Roboflow
    • 98.8%mAP, 76.3% precision, 99.2% recall

Version 6 (v6) - 391 images

  • Preprocessing: Auto-Orient and Resize (Stretch to 416x416), Modify Classes: 3 remapped, 2 dropped
    • Modified Classes: Class 0 = players, Class 1 = referree, Class 2 = futbol
      • Only Class 0, which was remapped to players was included in this version
  • Augmentations:
    • Outputs per training example: 3
    • Rotation: Between -25° and +25°
    • Shear: ±15° Horizontal, ±15° Vertical
    • Brightness: Between -25% and +25%
    • Blur: Up to 0.75px
    • Noise: Up to 1% of pixels
    • Bounding Box: Blur: Up to 0.5px
  • Training Metrics: Trained from Scratch (no transfer learning employed)
    • 95.5%mAP, 67.8% precision, 95.5% recall

Ilyes Talbi - LinkedIn | La revue IA

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{
                            futbol-players_dataset,
                            title = { futbol players Dataset },
                            type = { Open Source Dataset },
                            author = { Ilyes Talbi },
                            howpublished = { \url{ https://universe.roboflow.com/ilyes-talbi-ptwsp/futbol-players } },
                            url = { https://universe.roboflow.com/ilyes-talbi-ptwsp/futbol-players },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-02-21 },
                            }
                        

Connect Your Model With Program Logic

Find utilities and guides to help you start using the futbol players project in your project.

Source

Ilyes Talbi

Last Updated

2 years ago

Project Type

Object Detection

Subject

players-referee

Classes

0 1 2

Views: 4558

Views in previous 30 days: 177

Downloads: 88

Downloads in previous 30 days: 8

License

Public Domain