futbol players Computer Vision Project
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
- 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: 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
- 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: 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 2024-04-23 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the futbol players project in your project.