This project implements a real time object and face detection using YOLO algorithm. You only look once, or YOLO, is one of the fastet object detection algorithm, suitable for real-time detection. This repository contains code for object and face detector based on YOLOv3: An Incremental Improvement which originaly implemented in YOLOv3. The first part of this project focuses on object detection algorithm from scratch in pytorch using pre-trained weights. The second part and third part relate to the object detection and face detection algorithm using opencv library using yolo pre-trained weights.
- python 3.5
- Opencv 3.4.2
- pytorch
- numpy
To detect a single or multiple images, first clone the repository
git clone https://github.com/shayantaherian/Object-detection/Pytorch_ObjectDetection/.git
Then move to the directory
cd Pytorch_ObjectDetection
To run image detection
python detect.py
To run video and real-time webcame
python detect_video.py
Note that YOLO weights can be downloaded from yolov3.weights
OpenCV dnn module supports different pre-trained deep learning models and recently YOLO/Darknet has been added to opencv dnn module. To run the detector, first clone to the repository
git clone https://github.com/shayantaherian/Object-detection/OpenCV_ObjectDetection/.git
Then move to the directory
cd OpenCV_ObjectDetection
To run image detection
python yolo_Opencv.py
To run video and real-time webcame
python yolo_Opencv_video.py
To run the face detector, first clone to the repository
git clone https://github.com/shayantaherian/Object-detection/OpenCV_FaceDetection/.git
Then move to the directory
cd OpenCV_FacetDetection
Run the image detector
python yolo_Opencv_Face.py
Run the video/webcame detector
python yolo_Opencv_Face_video.py
Note that to use yolo for face detection it is required to download yolo face detection weight from yolov3.weights. An example of face detection on video:
