https://github.com/vybhav72954/human_detector

Boilerplate code for Human Detection, using Images
https://github.com/vybhav72954/human_detector

human-activity-recognition human-computer-interaction human-detection image image-processing opencv opensource

Last synced: about 2 months ago
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Boilerplate code for Human Detection, using Images

• Host: GitHub
• URL: https://github.com/vybhav72954/human_detector
• Owner: vybhav72954
• License: mit
• Created: 2020-12-09T13:41:15.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-12-11T18:19:31.000Z (over 5 years ago)
• Last Synced: 2025-06-09T13:52:27.874Z (about 1 year ago)
• Topics: human-activity-recognition, human-computer-interaction, human-detection, image, image-processing, opencv, opensource
• Language: Jupyter Notebook
• Homepage:
• Size: 7.31 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Human_Detector

A really basic (boilerplate) code for Human_detection using OpenCV.

The script `human_detector.py` is the Wrapper around, `HOG-SVM` model already implemented in OpenCV.

## Note

The aim of the script is not Accuracy, but ease of usability.

## Dependency

- OpenCV

- Numpy

- Imutils

- Jupyter

and associated packages.

These are summarised in `requirement.txt`

## Setup

1. A virtual environment (recommended)

1. `pip install -r requirements.txt`

1. Open the [Jupyter Notebook](human_detector.ipynb).

1. The Steps, details and guidelines can be found in comments.

## Output

- Using Images 

![](asset/output_img.PNG)

- Using Video

![](asset/output_video.gif)

## Disclaimer

- I have used the most basic SVM Histogram, as it is simple to implement.

- Accuracy is not the Aim

- The Script is as simple as it can be

## Author(s)  

Made by [Vybhav Chaturvedi](https://www.linkedin.com/in/vybhav-chaturvedi-0ba82614a/)