Implement object segmentation on images using HOG algorithm proposed in CVPR 2005

Last update: Mar 12, 2022

Overview

HOG Algorithm Implementation

Description

HOG (Histograms of Oriented Gradients) Algorithm is an algorithm aiming to realize object segmentation (edge detection) on images before CNN models are widely used.

Reference

Navneet Dalal and Bill Triggs, Histograms of Oriented Gradients, CVPR 2005

Getting Started

Clone this repository

git clone https://github.com/LeoTheBestCoder/HOG_implementation.git

Install related libraries

pip install opencv-python
pip install numpy
pip install matplotlib

Put your input image under same directory and modify line 10 in image.py (include filename extension)

IMAGE_NAME = 'amumu.jpg'

Run the script

python3 image.py

Demostration

Input Image
Segmentation Result

Owner

Leo Hsieh

I am studying Electrical Engineering in National Tsing Hua University at Hsinchu, Taiwan.

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Implement object segmentation on images using HOG algorithm proposed in CVPR 2005

Related tags

Overview

HOG Algorithm Implementation

Description

Reference

Getting Started

Demostration

Owner

Leo Hsieh

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