https://github.com/laurencee9/grgimage
C++ implementation of a networks converter from JPG images.
https://github.com/laurencee9/grgimage
geometric-algorithms image-converter network
Last synced: 6 months ago
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C++ implementation of a networks converter from JPG images.
- Host: GitHub
- URL: https://github.com/laurencee9/grgimage
- Owner: laurencee9
- License: mit
- Created: 2018-03-28T22:05:19.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-04-03T01:38:45.000Z (over 7 years ago)
- Last Synced: 2025-03-24T13:44:29.045Z (6 months ago)
- Topics: geometric-algorithms, image-converter, network
- Language: C++
- Homepage: http://edwardlaurence.me/portfolio/1993/01/11/facenetwork.html
- Size: 663 KB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Fast image to network generator
C++ implementation of a network converter from JPG images.
[Other examples](http://edwardlaurence.me/portfolio/1993/01/11/facenetwork.html)
## Usage
### Compilation
The two required packages are `boost::program_options` and `CImg`.
```
cd build
cmake ../src
make
```
`CImg` can be tricky to import with `cmake` depending on your machine. The current `CMakeLists.txt` has been tested on MacOSX 10.13.1. However, on Ubuntu, you may need to install the following packages:
```
apt-get install cmake libx11-dev libjpeg-dev cimg-dev gnuplot
```
### Creating networks
After compiling, the executable `GRGImage` should have been created in the `build` folder. The parameters are passed using `boost::program_options` so you can do
```
./GRGImage --help
```
to obtain a complete list of the parameters.
**List of parameters**
| Flag | Type | Description |
| ---------- |:-------------:| :-----|
| --imagePath (-i) | String | Path to the JPG image |
| --outputPath (-o) | String | Path to dump the output data (add prefix of data output) |
| --number_nodes (-N) | Int | Number of nodes in the resulting network|
| --degree (-d) | Int | Maximum degree of a node (usually 3 or 4)|
| --constrast | Float | Contrast parameter between -infinity to infinity. If positive, darker pixels will have a larger weight than lighter pixels. If you have a dark background, I suggest to use negative constrats. |
| --neigh (-n) | Int | maximum number of neighbor pixels that a node can connect to (for faster convergence) |
| --help || Show the parameters list|
|--transform | | Required to transform the network |
|--displayGray | | Not implemented |
|--CSV | | Output the data in CSV format |
|--GNU | | Output the data in a Gnuplot compatible format |
### Example
Examples have been made available in the `examples` folder.
For the glasses example, we run:
```
../build/GRGImage -i ./images/glasses.jpg -o ./data/glasses -N 1000 -d 3 --contrast 3.7 --transform --CSV --GNU
```
1000 nodes are enough to get a sharp image.
### Plotting
A Gnuplot script does the plotting for us. In the past, I used matplotlib but it was very slow (2-3 minutes for plotting). I also used a `d3.js` script to show the images in the browser that I could release if requested.
The Gnuplot script takes some parameters
| Params | Type | Description |
| ---------- |:-------------:| :-----|
| dat | String | Path to the dat file|
| o | String | Output path of the image (do not include the extension) |
|w | Int | Width of the original image (written on the dat file) |
|h| Int | Height of the original image (written on the dat file) |
|r | Float | The ratio between the output size and the original size |
|png| Int | If png=1, the image will be png|
|pdf| Int | If pdf=1, the image will be pdf|
|lw | Float | Linewidth of the edges |
An example is
```
gnuplot -e "dat='./data/glasses_width1200_height748.dat'; o='./networks/glasses';w=1200;h=748;r=1;png=1;lw=1.8" ../src/GNU_plot.gpi
```