SSTV generator in pure Python ============================= PySSTV generates SSTV modulated WAV files from any image that PIL can open (PNG, JPEG, GIF, and many others). These WAV files then can be played by any audio player connected to a shortwave radio for example. My main motivation was to understand the internals of SSTV in practice, so performance is far from optimal. I tried keeping the code readable, and only performed such optimizations that wouldn't have complicated the codebase. Command line usage ------------------ usage: run.py [-h] [--mode {MartinM2,MartinM1,Robot24BW,ScottieS2,ScottieS1,Robot8BW}] [--rate RATE] [--bits BITS] image.png output.wav Converts an image to an SSTV modulated WAV file. positional arguments: image.png input image file name output.wav output WAV file name optional arguments: -h, --help show this help message and exit --mode {MartinM2,MartinM1,Robot24BW,ScottieS2,ScottieS1,Robot8BW} image mode (default: Martin M1) --rate RATE sampling rate (default: 48000) --bits BITS bits per sample (default: 16) Python interface ---------------- The `SSTV` class in the `sstv` module implements basic SSTV-related functionality, and the classes of other modules such as `grayscale` and `color` extend this. Most instances implement the following methods: - `__init__` takes a PIL image, the samples per second, and the bits per sample as a parameter, but doesn't perform any hard calculations - `gen_freq_bits` generates tuples that describe a sine wave segment with frequency in Hz and duration in ms - `gen_values` generates samples between -1 and +1, performing sampling according to the samples per second value given during construction - `gen_samples` generates discrete samples, performing quantization according to the bits per sample value given during construction - `write_wav` writes the whole image to a Microsoft WAV file The above methods all build upon those above them, for example `write_wav` calls `gen_samples`, while latter calls `gen_values`, so typically, only the first and the last, maybe the last two should be called directly, the others are just listed here for the sake of completeness and to make the flow easier to understand. License ------- The whole project is available under MIT license. Useful links ------------ - receive-only "counterpart": https://github.com/windytan/slowrx - free SSTV handbook: http://www.sstv-handbook.com/ Dependencies ------------ - Python 2.7 (tested on 2.7.5) - Python Imaging Library (Debian/Ubuntu package: `python-imaging`)