SSIM-py

Structural Similarity (SSIM) index, where the core dependency is NumPy

To actually compare images with SSIM-py Pillow or opencv-python is needed

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Preparation

Setting up your environment

1. Download the SSIM-py.zip
2. Setup and activate a virtual environment (optional)
3. Extract the requirements.txt from the downloaded SSIM-py.zip
4. Open a command-line interface
5. Enter the following command on the command-line pip install -r requirements.txt

Result: Pillow, opencv-python and numpy modules are installed in the environment.

Image comparison preparation

Have two similar images ready to compare.

For the best result:

The module: opencv-python is preferred.

Make sure both images are the same size and have the same amount of color channels

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Usage

1. Open a command-line interface
2. Read the help text by entering the following command python SSIM-py.zip --help (optional)
3. Enter the following command python SSIM-py.zip path/to/image1 path/to/image2

Result: Number between 1 and 0 shows up on the command-line.

What to do by failure

Run the command again but now with the --verbose argument.

Copy the log into an textfile.

Usefull command to do this with is: python SSIM-py.zip --verbose path/to/image1 path/to/image2 > SSIM-py.log

Create an issue with the SSIM-py.log and the images used.

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Test information

Created and tested on Ubuntu 18.04.3 LTS

With python 3.6.8 (default, Oct 7 2019, 12:59:55) [GCC 8.3.0]

Pillow: 6.2.0

numpy: 1.17.3

opencv_python: 4.1.1.26

Tested with the following image formats: .tif .png .ppm .pgm .jpg .bmp

CAUTION: Comparing the same images with different file formats with Pillow won't give expected results.

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References

Thanks mom, Thanks dad.

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