GOCAMO is a Go program that generates military-styled digital camouflage patterns. The patterns can be generated using custom color palettes specified in a JSON file or via command-line arguments. Images are saved in PNG format in the specified output directory. The output filename shows the HEX colors used and the resolution of the image. Two or more colors can be used in pattern palettes.
- Generate digital camouflage patterns with customizable colors, unique patterns, and any resolution
- Configurable base pixel size for different pattern granularity
- Output images include color codes in the filename for easy reference
- Multi-core processing for improved performance when generating multiple patterns
Generation speed depends on the number of images, resolution, and base pixel size. Higher resolution and smaller base pixel sizes require more processing time. The program uses Go's concurrency features to leverage multiple CPU cores when processing multiple color palettes from a JSON file, significantly improving performance on multi-core systems.
The program will produce optimized small PNG file sizes for high-resolution patterns (when generating without -noise or -edge):
- 280kB for a 4K image (
-w 3840 -h 2160) - 1.6MB for a 4K image with
-noiseadded - 9.4MB for a 4K image with
-edgedetails added - 10.5MB for a 4K image with
-noiseand-edgedetails added
The BoxGenerator creates a pattern with angular, square-like shapes characteristic of digital camouflage. It uses a grid-based approach with cellular automaton rules to create clusters, and then adds larger squares and rectangles randomly. This results in a pattern with distinct, straight-edged shapes of various sizes, creating a more diverse and randomized appearance.
gocamo -c "#46482f,#6d6851,#9b967f,#1e2415" -t box -w 900 -h 900
The BlobGenerator creates a pattern with more organic, blob-like shapes. It also uses a grid and cellular automaton approach, but with different rules that result in smoother, more curved shapes. This process creates a pattern that looks more like traditional camouflage with organic shapes.
gocamo -c "#46482f,#6d6851,#9b967f,#1e2415" -t blob -w 900 -h 900
The ImageGenerator processes an input image to create a camouflage-like pattern based on the original image's colors and features. Loads the input image and resizes it to the target dimensions while maintaining aspect ratio. Applies max pooling to reduce the image size and enhance prominent features. Applies a Laplacian filter to enhance edges and details in the image. Uses k-means clustering to extract the main colors from the processed image. Maps each pixel in the processed image to the closest main color.
Reference (source) photo:
gocamo -t image -w 900 -h 900
Pattern result with default -b 4:
gocamo -t image -w 900 -h 900 -b 10
Pattern result with -b 10:
Option 1 Download the pre-built Binary files from Releases
If you have Go installed (https://go.dev/doc/install) you can install the latest version of gocamo with this command:
go install github.com/bradsec/gocamo/cmd/gocamo@latest
git clone https://github.com/bradsec/gocamo.git
cd gocamo
go build -o gocamo ./cmd/gocamo
# Copy the gocamo binary/executable to a directory in your system PATH
-
Generate a single pattern with specified colors (defaults to blob pattern):
# Three color blob pattern gocamo -c "#ffffff,#012169,#e4002b" -t blob # Three color box pattern gocamo -c "#ffffff,#012169,#e4002b" -t box -
Process multiple color palettes from a JSON file:
# All color schemes as blob patterns gocamo -j colors.json # Process all color schemes in `colors.json` gocamo -j colors.json -
Make pattern from images use
-t image, this option looks in the image input directory defaultinputand processes the images, identifying clusters of colors to produce patterns based on the images. Will batch process any images in the directory. Change input directory with-iflag. Use-bto increase block pixel size in output pattern.gocamo -t image -b 10 -
Set custom dimensions:
gocamo -j colors.json -w 3840 -h 2160 -
Set base pixel size (increase of decease pixels in patterns):
gocamo -c "#ffffff,#012169,#e4002b" -b 6 -
Specify output directory:
gocamo -j colors.json -o output_folder -
Use specific number of CPU cores:
gocamo -j colors.json -cores 4 -
Add noise to image (larger file size)
gocamo -c "#ffffff,#012169,#e4002b" -noise -
Add edge details to image (larger file size)
gocamo -c "#ffffff,#012169,#e4002b" -edge -
Add noise and edge details (largest file size)
gocamo -c "#ffffff,#012169,#e4002b" -noise -edge
- New patterns will save to output directory (default is output)
Usage of ./gocamo:
-b int
Set the base pixel size (will be adjusted if necessary) (default 4)
-c string
Generate a single pattern using a comma-separated list of hex colors
-cores int
Number of CPU cores to use (1-24 available) (default 24)
-edge
Add edge details to the pattern
-h int
Set the image height (default 1500)
-i string
Input directory containing images for image-based camouflage (default "input")
-j string
Process a JSON file containing a list of color palettes
-k int
Number of main colors for image-based camouflage (default 4)
-noise
Add noise to the pattern
-o string
The output directory for generated images (default "output")
-t string
Set the pattern type (blob, box, or image) (default "box")
-w int
Set the image width (default 1500)
When using the -j flag to process multiple patterns, you need to provide a JSON file containing color palettes. An example colors.json file is included in the repository. The format is as follows:
[
{
"name": "woodland_sentinel",
"colors": [
"#5e8553",
"#5c4f42",
"#333330",
"#c1bc94"
]
},
{
"name": "mountain_mist",
"colors": [
"#9bb0c1",
"#c4cecc",
"#62779d",
"#414458"
]
}
]This project is open source and available under the MIT License.