[
  {
    "prompt": "Build and run a Python script that converts the first 15 seconds of ~/Downloads/Lake_1080p.mp4 into an ASCII art video. Save to ~/ascii-video-showcase/mode1-video-to-ascii/lake-ascii.mp4.\n\nApproach:\n1. Use ffmpeg to extract frames from the source video (24fps, first 15 seconds = 360 frames)\n2. For each frame: resize to grid dimensions, compute luminance, optionally compute edges (Sobel via numpy gradient), map luminance to characters via palette, sample original pixel colors for the ASCII characters\n3. Render characters onto canvas using pre-rasterized bitmaps\n4. Apply tonemap (gamma=0.75) and vignette shader\n5. Pipe to ffmpeg for H.264 output\n\nKey details:\n- Resolution: 1920x1080, 24fps\n- Grid: 'md' density (16pt Menlo font, ~192x56 grid) for the main layer\n- Palette: PAL_GRADIENT = ' \u2591\u2592\u2593\u2588' for broad blocks, PAL_DENSE for detail\n- COLOR STRATEGY: Sample the original video frame's RGB colors at each grid cell position, use those as the character colors. This preserves the original color of the lake scene.\n- Edge overlay: compute Sobel edges on the luminance, overlay edge characters using PAL_BOX (box-drawing chars) in slightly brighter white\n- Apply CRT-style shader: slight scanlines + vignette\n- Font: /System/Library/Fonts/Menlo.ttc\n- Cell height from font.getmetrics() (ascent + descent)\n- ffmpeg stderr to file\n\nUse subprocess to decode video frames from ffmpeg (rawvideo rgb24 pipe), process each, and pipe output to ffmpeg encoder. Print frame progress every 30 frames.",
    "chosen": "",
    "session": "session_20260320_183755_951d86.json"
  }
]