Add streaming video compositor with sexp interpreter
- New streaming/ module for real-time video processing: - compositor.py: Main streaming compositor with cycle-crossfade - sexp_executor.py: Executes compiled sexp recipes in real-time - sexp_interp.py: Full S-expression interpreter for SLICE_ON Lambda - recipe_adapter.py: Bridges recipes to streaming compositor - sources.py: Video source with ffmpeg streaming - audio.py: Real-time audio analysis (energy, beats) - output.py: Preview (mpv) and file output with audio muxing - New templates/: - cycle-crossfade.sexp: Smooth zoom-based video cycling - process-pair.sexp: Dual-clip processing with effects - Key features: - Videos cycle in input-videos order (not definition order) - Cumulative whole-spin rotation - Zero-weight sources skip processing - Live audio-reactive effects - New effects: blend_multi for weighted layer compositing - Updated primitives and interpreter for streaming compatibility Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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gilesb
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streaming/sources.py
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281
streaming/sources.py
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"""
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Video and image sources with looping support.
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"""
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import numpy as np
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import subprocess
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import json
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from pathlib import Path
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from typing import Optional, Tuple
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from abc import ABC, abstractmethod
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class Source(ABC):
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"""Abstract base class for frame sources."""
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@abstractmethod
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def read_frame(self, t: float) -> np.ndarray:
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"""Read frame at time t (with looping if needed)."""
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pass
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@property
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@abstractmethod
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def duration(self) -> float:
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"""Source duration in seconds."""
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pass
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@property
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@abstractmethod
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def size(self) -> Tuple[int, int]:
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"""Frame size as (width, height)."""
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pass
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@property
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@abstractmethod
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def fps(self) -> float:
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"""Frames per second."""
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pass
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class VideoSource(Source):
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"""
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Video file source with automatic looping.
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Reads frames on-demand, seeking as needed. When time exceeds
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duration, wraps around (loops).
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"""
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def __init__(self, path: str, target_fps: float = 30):
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self.path = Path(path)
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self.target_fps = target_fps
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# Initialize decode state first (before _probe which could fail)
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self._process: Optional[subprocess.Popen] = None
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self._current_start: Optional[float] = None
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self._frame_buffer: Optional[np.ndarray] = None
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self._buffer_time: Optional[float] = None
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self._duration = None
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self._size = None
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self._fps = None
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if not self.path.exists():
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raise FileNotFoundError(f"Video not found: {path}")
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self._probe()
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def _probe(self):
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"""Get video metadata."""
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cmd = [
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"ffprobe", "-v", "quiet",
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"-print_format", "json",
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"-show_format", "-show_streams",
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str(self.path)
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]
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result = subprocess.run(cmd, capture_output=True, text=True)
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data = json.loads(result.stdout)
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# Get duration
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self._duration = float(data["format"]["duration"])
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# Get video stream info
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for stream in data["streams"]:
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if stream["codec_type"] == "video":
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self._size = (int(stream["width"]), int(stream["height"]))
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# Parse fps from r_frame_rate (e.g., "30/1" or "30000/1001")
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fps_parts = stream.get("r_frame_rate", "30/1").split("/")
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self._fps = float(fps_parts[0]) / float(fps_parts[1])
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break
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@property
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def duration(self) -> float:
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return self._duration
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@property
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def size(self) -> Tuple[int, int]:
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return self._size
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@property
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def fps(self) -> float:
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return self._fps
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def _start_decode(self, start_time: float):
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"""Start ffmpeg decode process from given time."""
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if self._process:
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try:
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self._process.stdout.close()
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except:
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pass
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self._process.terminate()
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try:
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self._process.wait(timeout=1)
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except:
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self._process.kill()
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self._process.wait()
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w, h = self._size
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cmd = [
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"ffmpeg", "-v", "quiet",
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"-ss", str(start_time),
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"-i", str(self.path),
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"-f", "rawvideo",
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"-pix_fmt", "rgb24",
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"-r", str(self.target_fps),
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"-"
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]
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self._process = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.DEVNULL,
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bufsize=w * h * 3 * 4, # Buffer a few frames
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)
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self._current_start = start_time
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self._buffer_time = start_time
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def read_frame(self, t: float) -> np.ndarray:
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"""
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Read frame at time t.
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If t exceeds duration, wraps around (loops).
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Seeks if needed, otherwise reads sequentially.
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"""
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# Wrap time for looping
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t_wrapped = t % self._duration
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# Check if we need to seek (loop point or large time jump)
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need_seek = (
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self._process is None or
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self._buffer_time is None or
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abs(t_wrapped - self._buffer_time) > 1.0 / self.target_fps * 2
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)
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if need_seek:
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self._start_decode(t_wrapped)
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# Read frame
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w, h = self._size
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frame_size = w * h * 3
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# Try to read with retries for seek settling
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for attempt in range(3):
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raw = self._process.stdout.read(frame_size)
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if len(raw) == frame_size:
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break
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# End of stream or seek not ready - restart from beginning
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self._start_decode(0)
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if len(raw) < frame_size:
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# Still no data - return last frame or black
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if self._frame_buffer is not None:
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return self._frame_buffer.copy()
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return np.zeros((h, w, 3), dtype=np.uint8)
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frame = np.frombuffer(raw, dtype=np.uint8).reshape((h, w, 3))
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self._frame_buffer = frame # Cache for fallback
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self._buffer_time = t_wrapped + 1.0 / self.target_fps
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return frame
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def close(self):
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"""Clean up resources."""
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if self._process:
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self._process.terminate()
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self._process.wait()
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self._process = None
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def __del__(self):
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self.close()
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def __repr__(self):
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return f"VideoSource({self.path.name}, {self._size[0]}x{self._size[1]}, {self._duration:.1f}s)"
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class ImageSource(Source):
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"""
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Static image source (returns same frame for any time).
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Useful for backgrounds, overlays, etc.
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"""
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def __init__(self, path: str):
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self.path = Path(path)
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if not self.path.exists():
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raise FileNotFoundError(f"Image not found: {path}")
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# Load image
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import cv2
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self._frame = cv2.imread(str(self.path))
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self._frame = cv2.cvtColor(self._frame, cv2.COLOR_BGR2RGB)
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self._size = (self._frame.shape[1], self._frame.shape[0])
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@property
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def duration(self) -> float:
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return float('inf') # Images last forever
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@property
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def size(self) -> Tuple[int, int]:
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return self._size
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@property
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def fps(self) -> float:
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return 30.0 # Arbitrary
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def read_frame(self, t: float) -> np.ndarray:
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return self._frame.copy()
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def __repr__(self):
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return f"ImageSource({self.path.name}, {self._size[0]}x{self._size[1]})"
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class LiveSource(Source):
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"""
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Live video capture source (webcam, capture card, etc.).
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Time parameter is ignored - always returns latest frame.
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"""
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def __init__(self, device: int = 0, size: Tuple[int, int] = (1280, 720), fps: float = 30):
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import cv2
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self._cap = cv2.VideoCapture(device)
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self._cap.set(cv2.CAP_PROP_FRAME_WIDTH, size[0])
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self._cap.set(cv2.CAP_PROP_FRAME_HEIGHT, size[1])
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self._cap.set(cv2.CAP_PROP_FPS, fps)
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# Get actual settings
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self._size = (
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int(self._cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
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int(self._cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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)
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self._fps = self._cap.get(cv2.CAP_PROP_FPS)
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if not self._cap.isOpened():
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raise RuntimeError(f"Could not open video device {device}")
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@property
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def duration(self) -> float:
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return float('inf') # Live - no duration
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@property
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def size(self) -> Tuple[int, int]:
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return self._size
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@property
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def fps(self) -> float:
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return self._fps
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def read_frame(self, t: float) -> np.ndarray:
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"""Read latest frame (t is ignored for live sources)."""
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import cv2
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ret, frame = self._cap.read()
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if not ret:
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return np.zeros((self._size[1], self._size[0], 3), dtype=np.uint8)
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return cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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def close(self):
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self._cap.release()
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def __del__(self):
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self.close()
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def __repr__(self):
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return f"LiveSource({self._size[0]}x{self._size[1]}, {self._fps}fps)"
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