Encode and decode slow-scan television (SSTV) transmissions in Python. This
package wraps the Rust sstv crate.
This package aims to be the definitive SSTV library for Python. Please create an issue or a pull request if you find a bug or are missing a feature.
Installation
pip install sstv
Usage
Decoding
sstv.decode_from_wav() takes a WAV recording and returns every SSTV image
found in it as a Pillow image:
import sstv
for image in sstv.decode_from_wav("recording.wav"):
image.save("decoded.png")
It accepts a path, in-memory WAV data (bytes), or a binary file-like
object. The sample rate is read from the WAV header, only the first channel
of multi-channel audio is used, and integer samples of any bit depth as
well as float samples are converted to 16 bit. sstv.decode_from_mp3() works
the same way for MP3 recordings.
For audio from other sources, sstv.decode() takes raw samples as a
one-dimensional numpy array — int16, or float32/float64 in
[-1.0, 1.0] — plus the sample rate:
import soundfile
samples, sample_rate = soundfile.read("recording.flac")
images = sstv.decode(samples[:, 0], sample_rate)
By default the mode of each transmission is detected from the VIS code in its header. Both can be overridden:
# The transmission is known to be Robot 36
images = sstv.decode(samples, sample_rate, mode=sstv.Mode.ROBOT_36)
# The recording starts directly at the first scanline (no header)
images = sstv.decode(samples, sample_rate, mode=sstv.Mode.ROBOT_36, header=False)
Both keyword arguments work the same on decode_from_wav() and decode_from_mp3().
Decode metadata is stored in each image's info dict:
image.info["sstv_mode"] # e.g. sstv.Mode.ROBOT_36 — which mode was detected
image.info["sstv_complete"] # False if the signal cut off mid-image;
# the rows the signal did not carry are black
Note that Pillow does not carry info through operations like crop or
resize, so read the metadata before transforming the image.
Encoding
sstv.encode_to_wav_file() turns an image into a WAV file;
sstv.encode_to_wav() returns the WAV data as bytes instead, and
sstv.encode() the raw int16 samples, e.g. for feeding an audio device:
from PIL import Image
photo = Image.open("photo.png").resize((320, 240))
sstv.encode_to_wav_file(photo, "out.wav", sstv.Mode.ROBOT_36)
data = sstv.encode_to_wav(photo, sstv.Mode.ROBOT_36)
samples = sstv.encode(photo, sstv.Mode.ROBOT_36, sample_rate=44_100)
sstv.encode_to_mp3() / sstv.encode_to_mp3_file() produce the
transmission as mono 128 kbit/s MP3 instead; their sample rate must be one
MP3 supports (8000-48000, see the docstring).
The image can be a PIL.Image (converted to RGB internally) or a
(height, width, 3) uint8 numpy array, and its dimensions must match the
mode's resolution — resize with
image.resize((mode.image_width, mode.image_height)). The transmission
includes the calibration header, so decoders can detect the mode.
Supported modes: Scottie 1/2/DX, Martin 1/2, Robot 36/72, Wrasse SC2-180, Pasokon P3/P5/P7, PD 50/90/120/160/180/240/290.
Development
Built with maturin. To build and test locally:
uv venv && uv pip install -e '.[dev]'
uv run pytest
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