https://github.com/MaybeShewill-CV/sky-detector

Sky area detection without deep neural networks https://maybeshewill-cv.github.io/sky-detector/
https://github.com/MaybeShewill-CV/sky-detector

image-segmentation opencv sky-area-detect sky-detection

Last synced: about 2 months ago
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Sky area detection without deep neural networks https://maybeshewill-cv.github.io/sky-detector/

• Host: GitHub
• URL: https://github.com/MaybeShewill-CV/sky-detector
• Owner: MaybeShewill-CV
• Created: 2018-07-16T12:26:15.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-04-02T06:49:46.000Z (over 4 years ago)
• Last Synced: 2024-05-02T11:13:47.416Z (5 months ago)
• Topics: image-segmentation, opencv, sky-area-detect, sky-detection
• Language: C++
• Homepage:
• Size: 3.04 MB
• Stars: 141
• Watchers: 8
• Forks: 44
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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README

        
# Sky-Area-Detector

sky area detection without deep neural networks.

A c++ implemention of the algorithm mentioned in paper 

"Sky Region Detection in a Single Image for Autonomous Ground

Robot Navigation". A fast and robust method to extract the 

sky area of an image.

  

# Installation

This implementation need opencv library. Since the project is 

static compiled for conveniently transplanting you need static

opencv library linked to this project. If static compilation is

not necessary for you feel free to modify the CMakeList to dynamic

compile the project.

This software has only been tested on ubuntu 16.04(x64), opencv3.4. 

To install this package your compiler need to support C++11. 

```

git clone https://github.com/MaybeShewill-CV/sky-detector.git

```

# Build

```

cd ROOT_FOLDER_DIR

mkdir build

cd build

cmake ..

make -j

```

The project will generate a static binary file which can be used

on other platform without any dynamic library. The binary file 

built on Ubuntu 16.04LTS was tested on CentOS 6 and worked 

correctly.

# Usage

```

cd build_dir

./detect input_image_file_path output_image_file_path

```

#### 结果示意图如下

`Test input image with full sky`

![Test_input_full_sky](/data/full_sky.png)

`Test input image with ful sky result`

![Test_input_full_sky_result](/data/ret_mask.jpg)

`Test input image with part sky`

![Test_input_part_sky](/data/partial_sky.png)

`Test input image with part sky result`

![Test_input_part_sky_result](/data/ret2.jpg)

# TODO

- [ ] Accelerate the calculation process