https://github.com/vijayg15/keras-facemask-detection-system
Face-mask detection system using YOLOv3 in Keras
https://github.com/vijayg15/keras-facemask-detection-system
artificial computer-vision convolutional-neural-networks covid19 deep-learning detection face-mask facemask-detection image-processing keras keras-neural-networks labelimg machine-learning neural-networks object-detection object-detection-keras tensorflow yolov3
Last synced: about 1 year ago
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Face-mask detection system using YOLOv3 in Keras
- Host: GitHub
- URL: https://github.com/vijayg15/keras-facemask-detection-system
- Owner: vijayg15
- Created: 2020-04-29T07:56:53.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-04-30T22:47:58.000Z (about 6 years ago)
- Last Synced: 2025-05-08T22:54:47.741Z (about 1 year ago)
- Topics: artificial, computer-vision, convolutional-neural-networks, covid19, deep-learning, detection, face-mask, facemask-detection, image-processing, keras, keras-neural-networks, labelimg, machine-learning, neural-networks, object-detection, object-detection-keras, tensorflow, yolov3
- Language: Python
- Size: 24.3 MB
- Stars: 14
- Watchers: 4
- Forks: 12
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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README
# FaceMask-Detection system using YOLOv3 in Keras
First of all, I must mention that this code used in this project originally is not mine. I was inspired by [qqwweee/keras-yolo3](https://github.com/qqwweee/keras-yolo3), he wrote this code to train custom YOLOv3 Keras model.
Few changes are:
1. To load images for detection, replaced PIL with opencv.
2. Used the same opencv font for drawing text on detected images.
3. Wrote seperate detection script for images and videos.
# Dependencies :
- Python 3.6.10
- Keras 2.2.4 `conda install keras=2.2.4`
- Tensorflow 1.15 `conda install tensorflow-gpu=1.15` or `conda install tensorflow`
- OpenCV-python
- PIL
- NumPy
- Moviepy(for the detection of videos) `pip install moviepy`
- LabelImg
Note that keras and tensorflow have their own dependencies. I recommend using [Anaconda](https://www.anaconda.com/) for handlinng the packages.
# Dataset :
I created the dataset for this project. It is divided into two categories ie "with_face_mask" and "without_face_mask". I downloaded the images for both categories from internet and saved them in respective folder in the local disk.
The most important part is the creation of Annotations and bounding boxes; for that purpose I used the [LabelImg](https://github.com/tzutalin/labelImg) annotation tool and created the labels and bounding boxes for each image.
In LabelImg, the annotations files are available in two format ie VOC format(XML file) or YOLO format. So, I got the data annotation file in YOLO format directly from labelImg ie [dataset_train.txt](YOLOv3/dataset_train.txt) file.
# Usage :
- Either download YOLOv3 weights from [YOLO website](https://pjreddie.com/media/files/yolov3.weights) & convert them, or download the YOLOv3 weights in keras format from [release section](https://github.com/vijayg15/FaceMask-Detection/releases/tag/yolo_weights).\
Copy downloaded weights file to "model_data" folder.
- Run the "train.py" file for training the model. (I opt batch_size = 4, increase the batch_size if have more memory). \
I tried to train with GTX1650, received memory error while using "batch_size = 32 or 16", was able to train with 4. \
Increase epochs count for better model accuracy.
- After finishing training, in "trained_weights/003/" folder there should be created new "trained_weights_final.h5" model file. \
This will be used for custom detection.
- Test YOLOv3 with images, use "image_detect.py" \
Simply change "model_path" and "classes_path", to the used files. Then at the end of file, change the test image name and directory.
- Test YOLOv3 with videos, use "video_detect.py" \
Simply change "model_path" and "classes_path", to the used files. Then at the end of file, just change the video and video_output directory.
# Screenshots :
# Video
#### I've also checked the final model on a video file. The output file can be seen [here](https://github.com/vijayg15/FaceMask-Detection/blob/master/Dataset/test/video1_output.mp4).