humecodec
FFmpeg integration for PyTorch with bundled libraries. Load and save audio/video files directly to PyTorch tensors without requiring a system FFmpeg installation.
Installation
pip install humecodec
The package includes bundled FFmpeg libraries, so no separate FFmpeg installation is required.
Quick Start
>>> import os, tempfile, math
>>> import torch
>>> import humecodec
>>> from humecodec import MediaDecoder, MediaEncoder, CodecConfig
>>> tmpdir = tempfile.mkdtemp()
Save Audio
>>> # Create a 1-second stereo 440 Hz sine wave
>>> sr = 44100
>>> t = torch.arange(sr, dtype=torch.float32) / sr
>>> sine = 0.5 * torch.sin(2 * math.pi * 440 * t)
>>> stereo = torch.stack([sine, sine], dim=0) # (2, 44100) — channels first
>>> stereo.shape
torch.Size([2, 44100])
>>> # Save as WAV, MP3, and FLAC
>>> wav_path = os.path.join(tmpdir, "test.wav")
>>> mp3_path = os.path.join(tmpdir, "test.mp3")
>>> flac_path = os.path.join(tmpdir, "test.flac")
>>> humecodec.save(wav_path, stereo, sr)
>>> humecodec.save(mp3_path, stereo, sr)
>>> humecodec.save(flac_path, stereo, sr)
Save Compressed Audio (Opus / bitrate)
The output codec is chosen from the file extension. Pass compression=CodecConfig(bit_rate=...)
to control the target bitrate for lossy codecs like Opus, MP3, or AAC. Opus always encodes at
48 kHz internally, so the input is resampled automatically.
>>> from humecodec import CodecConfig
>>> opus_path = os.path.join(tmpdir, "test.opus")
>>> humecodec.save(opus_path, stereo, sr, compression=CodecConfig(bit_rate=192000))
>>> humecodec.info(opus_path).codec
'opus'
compression also accepts a bare int/float as shorthand for the bitrate
(compression=192000 is equivalent to CodecConfig(bit_rate=192000)).
Load Audio
>>> # Load returns (waveform, sample_rate) with shape (channel, time)
>>> waveform, loaded_sr = humecodec.load(wav_path)
>>> loaded_sr
44100
>>> waveform.shape # (channels, time) — stereo
torch.Size([2, 44288])
>>> # Resample to 16 kHz
>>> waveform_16k, sr_16k = humecodec.load(wav_path, sample_rate=16000)
>>> sr_16k
16000
>>> # Slice: skip 0.1s, read 0.5s
>>> sliced, _ = humecodec.load(wav_path, frame_offset=4410, num_frames=22050)
>>> sliced.shape
torch.Size([2, 22050])
>>> # Downmix to mono
>>> mono, _ = humecodec.load(wav_path, num_channels=1)
>>> mono.shape[0]
1
Audio Info
>>> ai = humecodec.info(wav_path)
>>> ai.sample_rate
44100
>>> ai.num_channels
2
>>> ai
AudioInfo(sample_rate=44100, num_channels=2, ...)
Streaming Decode
>>> decoder = MediaDecoder(wav_path)
>>> decoder.add_audio_stream(frames_per_chunk=4096, buffer_chunk_size=3)
>>> chunks = [c for (c,) in decoder.stream() if c is not None]
>>> len(chunks)
11
>>> chunks[0].shape[1] # stereo
2
Streaming Encode
>>> enc_path = os.path.join(tmpdir, "encoded.wav")
>>> enc = MediaEncoder(enc_path)
>>> enc.add_audio_stream(sample_rate=44100, num_channels=1, format="flt")
>>> chunk = torch.zeros(4096, 1)
>>> with enc.open():
... enc.write_audio_chunk(0, chunk)
... enc.write_audio_chunk(0, chunk)
>>> ai = humecodec.info(enc_path)
>>> ai.sample_rate
44100
>>> ai.num_channels
1
Packet Index
>>> decoder = MediaDecoder(wav_path)
>>> decoder.add_audio_stream(frames_per_chunk=-1)
>>> index = decoder.build_packet_index(resolution=1)
>>> len(index)
11
>>> entry = index[0]
>>> entry.pts_seconds
0.0
>>> entry.pos # byte offset
78
>>> entry.size
16384
>>> entry.duration_seconds
0.09287981859410431
>>> total = sum(e.duration_seconds for e in index)
>>> total
1.004263038548753
Custom Filters
>>> decoder = MediaDecoder(wav_path)
>>> decoder.add_audio_stream(
... frames_per_chunk=-1,
... buffer_chunk_size=-1,
... filter_desc="aresample=16000,aformat=sample_fmts=fltp:channel_layouts=mono",
... )
>>> decoder.process_all_packets()
>>> (filtered,) = decoder.pop_chunks()
>>> filtered.shape[1] # mono
1
Video
Decode and encode video frames (requires video files, not tested here):
# Decode video
decoder = MediaDecoder("video.mp4")
decoder.add_video_stream(frames_per_chunk=1, format="rgb24")
for (frame,) in decoder.stream():
if frame is not None:
# frame shape: (1, 3, height, width)
print(f"Frame at {frame.pts:.2f}s")
# Encode video
encoder = MediaEncoder("output.mp4")
encoder.add_video_stream(
frame_rate=30.0, width=1920, height=1080,
format="rgb24", encoder="libx264",
encoder_option={"crf": "23", "preset": "medium"},
)
with encoder.open():
for frame in frames:
encoder.write_video_chunk(0, frame)
Query Functions
>>> humecodec.list_audio_backends()
['ffmpeg']
>>> versions = humecodec.get_versions()
>>> sorted(versions.keys())
['libavcodec', 'libavdevice', 'libavfilter', 'libavformat', 'libavutil']
>>> decoders = humecodec.get_audio_decoders()
>>> decoders["mp3"]
'MP3 (MPEG audio layer 3)'
>>> encoders = humecodec.get_audio_encoders()
>>> encoders["flac"]
'FLAC (Free Lossless Audio Codec)'
API Reference
Convenience Functions
| Function | Description |
|---|---|
load(uri, ...) |
Load audio file to tensor (channel, time) |
save(uri, src, sample_rate, ...) |
Save tensor to audio file |
info(path) |
Get audio file metadata (AudioInfo) |
list_audio_backends() |
Returns ["ffmpeg"] |
Classes
| Class | Description |
|---|---|
AudioInfo |
Metadata: sample_rate, num_channels, num_frames, codec, format, encoding, bits_per_sample |
MediaDecoder |
Streaming decoder for audio/video |
MediaEncoder |
Streaming encoder for audio/video |
CodecConfig |
Codec configuration (bit_rate, compression_level, qscale, gop_size, max_b_frames) |
Query Functions
| Function | Description |
|---|---|
get_audio_decoders() |
Available audio decoders |
get_audio_encoders() |
Available audio encoders |
get_video_decoders() |
Available video decoders |
get_video_encoders() |
Available video encoders |
get_demuxers() |
Available input formats |
get_muxers() |
Available output formats |
get_versions() |
FFmpeg library versions |
Tensor Formats
Audio
load()/save()default to channels-first:(channel, time)- Pass
channels_first=Falsefor(time, channel) - dtype:
torch.float32, range[-1.0, 1.0] MediaDecoder/MediaEncoderuse(time, channel)natively
Video
- Shape:
(num_frames, channels, height, width) - dtype:
torch.uint8for RGB/BGR,torch.float32for YUV - RGB24:
(N, 3, H, W), values[0, 255]
Building from Source
git clone https://github.com/your-org/humecodec
cd humecodec
# Editable install (auto-fetches prebuilt FFmpeg if needed)
pip install -e .
# Or with custom FFmpeg location
HUMECODEC_FFMPEG_ROOT=/path/to/ffmpeg pip install -e .
License
BSD-3-Clause
This project bundles FFmpeg libraries which are licensed under LGPL/GPL. See FFmpeg's license for details.
1 maintainer
Release files for humecodec 0.9.0
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