capture-helper 0.2.4

Capture Helper — OBS-inspired (no GUI) capture, processing, and publishing for the AI Helpers stack. Multi-surface: library + argparse CLI + click CLI + FastAPI HTTP surface + MCP tools over the INPUT layer (cameras / microphones).

Capture Helper

🇫🇷 · 🇬🇧

Capture Helper belongs to a collection of libraries called AI Helpers developed for building Artificial Intelligence.

OBS-inspired (no GUI) capture + processing + publishing layer for the AI Helpers stack. Library-shaped: cross-platform camera / microphone / screen / window / application-audio sources, composable filter chains, multi-source mixing, and emit-to-publish primitives for live YouTube / Twitch RTMP, HLS, and Icecast — designed to plug into video-helper and podcast-helper for downstream frame / PCM contracts.

🌍 AI Helpers

Documentation

💻 Documentation

📋 Examples

Status — v0.1.0 INPUT layer

What ships today:

• SourceKind literal ("camera" | "microphone")
• Source typed dict (kind, name, index, platform, driver)
• MicFrame typed dict (mirrors podcast_helper.PcmFrame)
• list_sources(kind=None) — cross-platform device enumeration via ffmpeg -list_devices (macOS avfoundation / Windows dshow / Linux v4l2 + pulse)
• pick_source(kind, *, name_substring=..., index=...) — pick the first matching device, raises ValueError if nothing matches
• iter_camera_frames(source, *, width=..., height=..., output_width=..., output_height=..., fps=..., max_frames=...) — yields (H, W, 3) BGR uint8 numpy arrays, same contract as video_helper.extract_frames
• iter_mic_audio(source, *, target_sample_rate=16000, to_mono=True, frame_ms=20) — async iterator yielding MicFrames, same contract as podcast_helper.extract_audio_stream
• ffmpeg_input_args(source) — exposed low-level helper for users wiring their own ffmpeg pipelines

import asyncio
import capture_helper as ch

# Enumerate available devices
for s in ch.list_sources():
    print(f"{s['kind']:10s} [{s['index']}] {s['name']:40s} (driver={s['driver']})")
    # camera     [0] FaceTime HD Camera                       (driver=avfoundation)
    # microphone [0] Built-in Microphone                      (driver=avfoundation)

# Camera → numpy BGR frames (drop-in for video_helper.extract_frames)
cam = ch.pick_source("camera")
for frame in ch.iter_camera_frames(cam, output_width=640, output_height=360,
                                   fps=30, max_frames=300):
    # frame.shape == (360, 640, 3), dtype uint8, BGR.
    do_something(frame)

# Microphone → async PCM stream (drop-in for podcast_helper.extract_audio_stream)
async def listen():
    mic = ch.pick_source("microphone")
    async for f in ch.iter_mic_audio(mic, target_sample_rate=16000,
                                     to_mono=True, frame_ms=20):
        # f["pcm"].shape == (320,) — 20ms @ 16kHz mono.
        await asr.feed(f["pcm"])
asyncio.run(listen())

Roadmap

Version	Layer	Scope
v0.0.1	INPUT scaffold	list_sources + types
v0.1.0 (this release)	INPUT	pick_source(...) + iter_camera_frames(source, ...) + iter_mic_audio(source, ...) — composes with video-helper / podcast-helper contracts
v0.2.0	INPUT extended	Screen / window capture; basic filter chain (noise gate, gain, scale)
v0.3.0	PROCESS	Scenes / mixer — mix_audio([sources], levels=[...]) + compose_video([sources], layout=...)
v0.4.0	PUBLISH	emit_to_youtube_live(...), emit_to_twitch_live(...), emit_to_rtmp(...), emit_to_hls(...), emit_audio_to_icecast(...)
v0.5.0	OUTPUT virtual	output_to_virtual_camera(...) (pyvirtualcam etc.), output_to_virtual_mic(...)
v0.6.0	OBS integration	OBS WebSocket client (react to scene / stream events)

For a full cookbook (per-OS ffmpeg input strings, snapshot capture, live preview, ASR / VAD wiring), see 📋 EXAMPLES.md.

Multi-surface exposure

capture-helper ships the same INPUT layer through five surfaces so it plugs in wherever you already work — no rewrite needed.

Surface	Install	Entry point	Use case
Python library	pip install capture-helper	import capture_helper as ch	Notebooks, scripts, other AI Helpers
argparse CLI	(no extra)	capture-helper …	Shells, cron, CI, container CMD
click CLI	[cli] extra	capture-helper-click …	Users on a click-native stack (completion, colored --help)
FastAPI HTTP	[api] extra	uvicorn capture_helper.api:app	Reverse-proxied service, JSON / multipart clients
MCP tools	[api,mcp] extras	capture-helper-mcp	LLM agents (Claude Desktop, custom MCP clients)

# CLI (argparse — always available)
capture-helper list-sources
capture-helper pick-source --kind camera --name FaceTime
capture-helper capture-mic --output mic.wav --seconds 3

# CLI (click twin — same subcommands)
capture-helper-click list-sources
capture-helper-click capture-camera --output-dir frames/ \
    --output-width 640 --output-height 360 --max-frames 30

# HTTP surface
uvicorn capture_helper.api:app --host 0.0.0.0 --port 8000
curl http://localhost:8000/sources
curl -o frames.zip \
    'http://localhost:8000/capture/camera?output_width=320&output_height=240&max_frames=10'

# MCP surface (FastAPI + fastapi-mcp)
capture-helper-mcp   # serves HTTP routes + MCP endpoint on :8000

# Docker (ships FastAPI + MCP by default)
docker build -t capture-helper .
docker run --rm -p 8000:8000 capture-helper

For a GUI vision (device wall + PGM/PVW cueing, not a CLI mirror), see 📋 GUI.md. For a competitive comparison against OpenCV / PyAV / sounddevice / OBS / FFmpeg CLI / GStreamer, see 📋 LANDSCAPE.md.

Installation

Prerequisites — Python 3.10–3.13 and git, ffmpeg, PortAudio, cross-platform:

• 🍎 macOS (Homebrew): brew install python git ffmpeg portaudio
• 🐧 Ubuntu/Debian: sudo apt update && sudo apt install -y python3 python3-pip git ffmpeg portaudio19-dev
• 🪟 Windows (PowerShell): winget install Python.Python.3.12 Git.Git Gyan.FFmpeg (PortAudio ships inside the Python wheels)

We recommend using Python environments. Check this link if you're unfamiliar with setting one up: 🥸 Tech tips.

You still need ffmpeg on PATH for device enumeration and live capture to return anything.

From PyPI (recommended)

# Core INPUT layer (list/pick sources, camera + mic iterators)
pip install capture-helper

# Optional surfaces
pip install "capture-helper[cli]"       # click-based CLI twin
pip install "capture-helper[api]"       # FastAPI HTTP surface
pip install "capture-helper[api,mcp]"   # MCP tools over FastAPI

From source (no PyPI)

# Core INPUT layer
pip install "git+https://github.com/warith-harchaoui/capture-helper.git@v0.2.4"

# Optional surfaces
pip install "capture-helper[cli] @ git+https://github.com/warith-harchaoui/capture-helper.git@v0.2.4"
pip install "capture-helper[api] @ git+https://github.com/warith-harchaoui/capture-helper.git@v0.2.4"
pip install "capture-helper[api,mcp] @ git+https://github.com/warith-harchaoui/capture-helper.git@v0.2.4"

Author

• Warith HARCHAOUI

Acknowledgements

Special thanks to Mohamed Chelali and Bachir Zerroug for fruitful discussions.

License

This project is licensed under the BSD-3-Clause License — see the LICENSE file for details.