Real-Time Object Detection Using Yolov2 and Distance Estimation

This project repository provides a means that can be used to find the distance of an object or an indication of how close the object is, to the camera lens. The codes present in this perfume are simply attempts to scan deep concepts for calculating the distance of objects from camera lenses.

Real-Time Object Detection and Distance Estimation GUI

Object Detection Distance Estimation Bench 1
Object Detection Distance Estimation Bench 2
Object Detection Distance Estimation Bench 3
Object Detection Distance Estimation Bench 4

YOLOv2

You only look once (YOLO) is an object detection system targeted for real-time processing. We will introduce YOLO, YOLOv2 and YOLO9000 in this article. For those only interested in YOLOv3, please forward to the bottom of the article. Here is the accuracy and speed comparison provided by the YOLO web site.

Requirement

• OpenCV 4.2.0
• Python 3.7

Quick start

• Download official yolov3.weights and place it under a folder called weight.
• Download yolov2.cfg and place it under a folder called cfg.

Dependencies

• opencv
• numpy

Install dependencies

pip install numpy opencv-python

How to use?

1. Clone the repository

git clone https://github.com/muhammadshiraz/Real-time-object-detection-using-yolov2-and-distance-estimation.git

2. Move to the directory

cd Real-time-object-detection-using-yolov2-and-distance-estimation

3. To view the object detection distance estimation bench 1

python Object_Detection_Distance_Estimation_Bench_1.py

4. To view the object detection distance estimation bench 2

python Object_Detection_Distance_Estimation_Bench_2.py

5. To view the object detection distance estimation bench 3

python Object_Detection_Distance_Estimation_Bench_3.py

6. To view the object detection distance estimation bench 4

python Object_Detection_Distance_Estimation_Bench_4.py

Run by PyCharm IDE:

Object Detection Distance Estimation