Mohamed Traore

Face Detection

Object Detection


Face Detection Computer Vision Project

Drop an image or


1369 images
Explore Dataset

Background Information

This dataset was curated and annotated by Mohamed Traore and Justin Brady after forking the raw images from the Roboflow Universe Mask Wearing dataset and remapping the mask and no-mask classes to face.

Example Image from the Dataset

The main objective is to identify human faces in images or video. However, this model could be used for privacy purposes with changing the output of the bounding boxes to blur the detected face or fill it with a black box.

The original custom dataset (v1) is composed of 867 unaugmented (raw) images of people in various environments. 55 of the images are marked as Null to help with feature extraction and reducing false detections.

Version 2 (v2) includes the augmented and trained version of the model. This version is trained from the COCO model checkpoint to take advantage of transfer learning and improve initial model training results.

Model Updates:

After a few trainings, and running tests with Roboflow's webcam model and Roboflow's video inference repo, it was clear that edge cases like hands sometimes recognized as faces was an issue. I grabbed some images from Alex Wong's Hand Signs dataset (96 images from the dataset) and added them to the project. I uploaded the images, without the annotation files, labeled all the faces, and retrained the model (version 5).

The dataset is available under the CC BY 4.0 license.

Includes images from:

@misc{ person-hgivm_dataset,
    title = { person Dataset },
    type = { Open Source Dataset },
    author = { Abner },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2021 },
    month = { aug },
    note = { visited on 2022-10-14 },

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.


This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.


This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Connect Your Model With Program Logic

Find utilities and guides to help you start using the Face Detection project in your project.

Last Updated

a day ago

Project Type

Object Detection




Views: 64376

Views in previous 30 days: 3596

Downloads: 3522

Downloads in previous 30 days: 238


CC BY 4.0