face-mask-detection
In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building. [Moved to: https://github.com/datarootsio/tutorial-face-mask-detection] (by datarootsio)
tutorial-face-mask-detection
In this project, we develop a pipeline to detect unmasked faces in images. This can, for example, be used to alert people that do not wear a mask when entering a building. (by datarootsio)
| face-mask-detection | tutorial-face-mask-detection | |
|---|---|---|
| 1 | 1 | |
| 86 | 86 | |
| - | - | |
| 10.0 | 10.0 | |
| almost 2 years ago | over 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
face-mask-detection
Posts with mentions or reviews of face-mask-detection.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-29.
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Face Mask Detection - tutorial
git clone https://github.com/datarootsio/face-mask-detection.git cd face-mask-detection mkdir data tar -xvf data.tar.gz -C ./data pip install -r requirements.txt
tutorial-face-mask-detection
Posts with mentions or reviews of tutorial-face-mask-detection.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-29.
-
Face Mask Detection - tutorial
Our validation and testing data consists of images of people with and without masks that we collected from various sources that provide images with permissive licences (e.g. pexels.com, unsplash.com). We have manually annotated all faces in the collected images, and labeled them as being masked or not (using the makesense.ai annotation tool). We collected 273 images which contain 524 faces (246 masked and 278 non-masked). The images are split 50/50 over the validation set and test set. An overview of the collected data and corresponding URLs and ground truth annotations can be found in test_validation_metadata.csv.
What are some alternatives?
When comparing face-mask-detection and tutorial-face-mask-detection you can also consider the following projects:
Playing-Cards-Classification-TensorFlow-CNN - CNN Model to Classify Playing Cards
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.
DSFD-Pytorch-Inference - A High-Performance Pytorch Implementation of face detection models, including RetinaFace and DSFD
Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.
Face-Mask-Detection - Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
observations
Steganography - Hiding Text and Image inside an Image
face-mask-detection vs Playing-Cards-Classification-TensorFlow-CNN
tutorial-face-mask-detection vs One-Piece-Image-Classifier
face-mask-detection vs DSFD-Pytorch-Inference
tutorial-face-mask-detection vs Human-pose-estimation
face-mask-detection vs Face-Mask-Detection
tutorial-face-mask-detection vs DSFD-Pytorch-Inference
face-mask-detection vs One-Piece-Image-Classifier
tutorial-face-mask-detection vs Playing-Cards-Classification-TensorFlow-CNN
face-mask-detection vs observations
tutorial-face-mask-detection vs Steganography
tutorial-face-mask-detection vs observations
tutorial-face-mask-detection vs Face-Mask-Detection