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

Related tags

Deep Learning computer-vision edge-detection object-segmentation
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

  1. Clone this repository
git clone https://github.com/LeoTheBestCoder/HOG_implementation.git
  1. Install related libraries
pip install opencv-python
pip install numpy
pip install matplotlib
  1. Put your input image under same directory and modify line 10 in image.py (include filename extension)
IMAGE_NAME = 'amumu.jpg'
  1. Run the script
python3 image.py

Demostration

  • Input Image
  • Segmentation Result
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Owner
Leo Hsieh
I am studying Electrical Engineering in National Tsing Hua University at Hsinchu, Taiwan.
Leo Hsieh
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