https://github.com/NisargPethani/FACE-MASK-DETECTION-USING-YOLO-V3
Using PyTorch Framework
https://github.com/NisargPethani/FACE-MASK-DETECTION-USING-YOLO-V3
Last synced: about 2 months ago
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Using PyTorch Framework
- Host: GitHub
- URL: https://github.com/NisargPethani/FACE-MASK-DETECTION-USING-YOLO-V3
- Owner: NisargPethani
- Created: 2020-05-11T10:52:11.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2024-07-25T10:59:12.000Z (11 months ago)
- Last Synced: 2024-11-09T16:44:22.481Z (7 months ago)
- Language: Python
- Size: 7.84 MB
- Stars: 18
- Watchers: 1
- Forks: 16
- Open Issues: 6
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-yolo-object-detection - NisargPethani/FACE-MASK-DETECTION-USING-YOLO-V3 - MASK-DETECTION-USING-YOLO-V3?style=social"/> : FACE-MASK DETECTION. (Object Detection Applications)
- awesome-yolo-object-detection - NisargPethani/FACE-MASK-DETECTION-USING-YOLO-V3 - MASK-DETECTION-USING-YOLO-V3?style=social"/> : FACE-MASK DETECTION. (Applications)
README
# FACE-MASK DETECTION
A minimal PyTorch implementation of YOLOv3, with support for training, interface & evalution.
To train on custom dataset please visit my another [[GitRepo]]().
## ABSTARCT
### APPROCH
Standard YOLO V3 Approch is modified, and the table shows what change has been made.
|Standard YOLO Approch | Self-Modified YOLO Approch |
|-----------------------------------------------|--------------------------------------------------|
| 1. Object Detection Process | 1. Object Detection Process |
| ... 1.1. Localization | ... 1.1. Localization |
| ... 1.2. Class Prediction | ... 1.2. Class Prediction |
| 2. Thresholding | 2. Thresholding |
| 3. Non max suppression with respect to Class | 3. Non max suppression irrespective of class label|
||4. Bounding Box Labelling|
### REPORT
- Explanation : [explanation.md](explanation.md)
- You can check the full report of this project here... [[FACE-MASK DETECTION USING YOLO V3 ARCHITECTURE.pdf]](https://drive.google.com/file/d/1QFFEEtHlMsQHcgEiQYy4hlYvCam73KE5/view?usp=sharing)
## INSTALLATION
##### Clone and install requirements
> git clone https://github.com/NisargPethani/Face-Mask-Detection-using-YOLO-v3.git
> cd Face-Mask-Detection-using-YOLO-v3/
> pip install -r requirements.txt
##### Checkpoints
Download checkpoint From [[GoogleDrive]](https://drive.google.com/drive/folders/1UlF6PmTwwd4cm-wD9v6Qy7gbC_tzif_j?usp=sharing)
Copy `yolov3_ckpt_35.pth` into `checkpoints/`
## EVALUATION
Evaluates the model.
> python validate.py --weights_path checkpoints/yolov3_ckpt_35.pth
Average Precisions:
| Class | AP |
| ----------------------- |:-----------------:|
| Class '0' (MASK) | 73.0 |
| Class '1' (NO_MASK) | 83.3 |
mAP: 78.19
## DETECTION
### Real Time Detection
> python cam_detect.py --weights_path checkpoints/yolov3_ckpt_35.pth
Some Screen-shots of Real-Time Detection is shown below
### Detection in Image
Move inmages to `testing/input/images`
> python image_detect.py --image_folder testing/input/images --weights_path checkpoints/yolov3_ckpt_35.pth
### Detection in Video
Make new directory with name: `'videos'` in `testing/input`
Move videos to `testing/input/videos`
> python video_detect.py --image_folder testing/input/videos --weights_path checkpoints/yolov3_ckpt_35.pth
## YOUTUBE
Following YouTube video shows the output.
## CREDIT
[[Paper]](https://pjreddie.com/media/files/papers/YOLOv3.pdf) [[Project Webpage]](https://pjreddie.com/darknet/yolo/) [[Authors' Implementation]](https://github.com/pjreddie/darknet)
```
@article{yolov3,
title={YOLOv3: An Incremental Improvement},
author={Redmon, Joseph and Farhadi, Ali},
journal = {arXiv},
year={2018}
}
```
Also Help is taken from [[GitRepo]](https://github.com/eriklindernoren/PyTorch-YOLOv3.git)