https://github.com/iyashwantsaini/multiple-object-detection
An OpenCV based object detection system to detect objects like cars and pedestrians in a video using Python, OpenCV and Numpy
https://github.com/iyashwantsaini/multiple-object-detection
Last synced: 3 months ago
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An OpenCV based object detection system to detect objects like cars and pedestrians in a video using Python, OpenCV and Numpy
- Host: GitHub
- URL: https://github.com/iyashwantsaini/multiple-object-detection
- Owner: iyashwantsaini
- License: mit
- Created: 2019-08-21T20:02:57.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-10-20T14:09:58.000Z (over 5 years ago)
- Last Synced: 2025-01-16T22:29:37.464Z (5 months ago)
- Language: Python
- Homepage:
- Size: 11.7 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Multiple object detection
An OpenCV based object detection system to detect objects like cars and pedestrians in a video .
# OpenCV
OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library.
OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products.
Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.
# Numpy
NumPy is the fundamental package for scientific computing with Python. It contains among other things:
1. a powerful N-dimensional array object
2. sophisticated (broadcasting) functions
3. tools for integrating C/C++ and Fortran code
4. useful linear algebra, Fourier transform, and random number capabilities
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
# Requirements
OpenCV , Numpy
# Running code
1. install OpenCV , Numpy
2. run the script using following command : python file_name_here.py
3. press ENTER to exit the app.