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README.md
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README.md
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# 🌌 ASCILINE Engine
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# 🌌 ASCILINE Engine with Export
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**ASCILINE** is a high-performance, cross-platform real-time ASCII video rendering engine. **Our core objective is to transform the web into a highly dynamic and interactive typographic canvas.** By mapping pixels to text-based representations, we unlock new possibilities for web media delivery.
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## 💾 Export to Static Files (`export_ascii.py`)
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Export any video to two portable static files — no server or WebSocket required:
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| File | Contents |
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| :--- | :--- |
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| `output.txt` | Plain ASCII frames separated by dividers. Human-readable, terminal-pipeable, embeddable in `.md`. |
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| `output.ascjson` | Compact JSON with per-cell color data: `{"meta":{cols,rows,fps},"frames":[[char,r,g,b,...]...]}`. Feeds the web player widget directly. |
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Place `export_ascii.py` in the ASCILINE folder (next to `ascii_video_player2.py`), then:
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```bash
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# Basic — outputs video.txt + video.ascjson
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python export_ascii.py video.mp4
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# Custom output name
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python export_ascii.py video.mp4 -o my_export
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# Custom grid size (rows auto-calculated if omitted)
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python export_ascii.py video.mp4 --cols 120 --rows 34
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# Cap output FPS (default: 24)
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python export_ascii.py video.mp4 --max-fps 12
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# Text only, skip the color JSON
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python export_ascii.py video.mp4 --no-color
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# Suppress progress output
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python export_ascii.py video.mp4 --quiet
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```
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### Web Player Widget
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Load an `.ascjson` export into any webpage with the included `website_widget.js`:
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```html
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<!-- 1. Add a container -->
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<div id="my-player"></div>
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<!-- 2. Load the widget script -->
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<script src="website_widget.js"></script>
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<!-- 3. Initialize -->
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<script>
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AscilineWidget.init('#my-player', {
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src: 'video.ascjson',
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autoplay: true,
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loop: true,
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color: true,
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});
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</script>
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```
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| Output | Details |
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| :--- | :--- |
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| <img src="https://github.com/user-attachments/assets/ccc727c9-c697-49f2-85e1-6f8c366f2019" width="400" alt="Original Source" /> | **Original Source**<br>Standard MP4 video file. |
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1026
asciline_studio.html
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asciline_studio.html
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export_ascii.py
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export_ascii.py
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"""
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export_ascii.py — Export ASCILINE video frames to static files
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==============================================================
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Outputs files from a video in two modes:
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ASCII mode (default):
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1. <output>.txt — Plain ASCII text, one frame per section
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2. <output>.ascjson — JSON with char+RGB per cell
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PIXEL mode (--pixel):
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1. <output>.txt — Full-block █ with ANSI 24-bit color codes
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2. <output>.ascjson — Compact JSON, RGB only (3 bytes/cell, 16M colors)
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Structure: {"meta":{cols,rows,fps,mode:"pixel"},
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"frames":[[r,g,b,...]...]}
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Usage:
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python export_ascii.py myvideo.mp4
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python export_ascii.py myvideo.mp4 --pixel --cols 320 --max-fps 15
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python export_ascii.py myvideo.mp4 --pixel --no-color # txt only
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Dependencies: opencv-python numpy
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Place this file next to ascii_video_player2.py
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"""
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import sys
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import os
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import json
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import argparse
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import numpy as np
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# ── resolve ASCILINE root ─────────────────────────────────────────────────────
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SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
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sys.path.insert(0, SCRIPT_DIR)
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try:
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from ascii_video_player2 import VideoDecoder, AsciiMapper
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except ImportError:
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print("ERROR: ascii_video_player2.py not found. Place export_ascii.py in the ASCILINE folder.")
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sys.exit(1)
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# ── palette (mirrors ASCILINE default) ───────────────────────────────────────
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PALETTE = list(" `.-':_,^=;><+!rc*/z?sLTv)J7(|Fi{C}fI31tlu[neoZ5Yxjya]2ESwqkP6h9d4VpOGbUAKXHm8RD#$Bg0MNWQ%&@")
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FRAME_SEP = "─" * 80
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# ── ANSI 24-bit color helpers ────────────────────────────────────────────────
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ANSI_FG = "\033[38;2;{};{};{}m"
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ANSI_BG = "\033[48;2;{};{};{}m"
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ANSI_RESET = "\033[0m"
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FULL_BLOCK = "\u2588" # █
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def calc_rows(cols, vid_w, vid_h):
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"""Match ASCILINE's auto-row formula (chars are ~2× taller than wide)."""
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ratio = vid_w / max(vid_h, 1)
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return max(1, round(cols / ratio / 2))
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def export(video_path: str, output_stem: str, cols: int, rows: int | None,
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no_color: bool, max_fps: float, progress: bool, pixel_mode: bool):
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# ── Open once to get dimensions ───────────────────────────────────────
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probe = VideoDecoder(video_path, cols, rows or 1)
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vid_w, vid_h = probe.vid_w, probe.vid_h
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probe.release()
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if rows is None:
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rows = calc_rows(cols, vid_w, vid_h)
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decoder = VideoDecoder(video_path, cols, rows)
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fps = min(decoder.fps, max_fps)
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skip_n = max(1, round(decoder.fps / fps)) if decoder.fps > max_fps else 1
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effective_fps = decoder.fps / skip_n
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mode_label = "PIXEL" if pixel_mode else "ASCII"
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# ── ASCII mode setup ──────────────────────────────────────────────────
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if not pixel_mode:
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mapper = AsciiMapper(PALETTE)
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n = mapper._n
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lut = mapper._lut
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char_byte_lut = np.array([ord(c) for c in lut], dtype=np.uint8)
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txt_path = output_stem + ".txt"
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json_path = output_stem + ".ascjson"
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print(f"Video : {video_path}")
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print(f"Grid : {cols}×{rows} FPS: {effective_fps:.1f} Mode: {mode_label}")
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print(f"Output: {txt_path}")
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if not no_color:
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print(f" {json_path}")
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txt_frames = []
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json_frames = []
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frame_idx = 0
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try:
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while True:
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# FPS decimation
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for _ in range(skip_n - 1):
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if not decoder.grab():
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decoder.release()
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break
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try:
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gray, bgr = next(decoder)
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except StopIteration:
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break
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if pixel_mode:
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# ═══════════════════════════════════════════════════════════
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# PIXEL MODE — solid color blocks, 16M color fidelity
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# ═══════════════════════════════════════════════════════════
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rgb = bgr[:, :, ::-1].copy() # BGR → RGB, shape (rows, cols, 3)
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# ── .txt with ANSI 24-bit color ───────────────────────────
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lines = []
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for r in range(rows):
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parts = []
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for c in range(cols):
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pr, pg, pb = int(rgb[r, c, 0]), int(rgb[r, c, 1]), int(rgb[r, c, 2])
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parts.append(f"{ANSI_FG.format(pr, pg, pb)}{FULL_BLOCK}")
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parts.append(ANSI_RESET)
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lines.append(''.join(parts))
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txt_frames.append(f"FRAME {frame_idx}\n" + '\n'.join(lines))
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# ── .ascjson — RGB only, 3 values per cell ────────────────
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if not no_color:
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json_frames.append(rgb.flatten().tolist())
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else:
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# ═══════════════════════════════════════════════════════════
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# ASCII MODE — character density + color (original)
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# ═══════════════════════════════════════════════════════════
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indices = np.floor_divide(gray, max(1, 256 // n))
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np.clip(indices, 0, n - 1, out=indices)
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char_matrix = lut[indices]
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lines = [''.join(row) for row in char_matrix]
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txt_frames.append(f"FRAME {frame_idx}\n" + '\n'.join(lines))
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if not no_color:
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char_codes = char_byte_lut[indices]
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rgb = bgr[:, :, ::-1].copy()
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frame_buf = np.empty((rows, cols, 4), dtype=np.uint8)
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frame_buf[:, :, 0] = char_codes
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frame_buf[:, :, 1:] = rgb
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json_frames.append(frame_buf.flatten().tolist())
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frame_idx += 1
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if progress and frame_idx % 50 == 0:
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total = decoder.frame_count
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pct = min(100, round(frame_idx * skip_n / total * 100))
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print(f" … {frame_idx} frames ({pct}%)", end='\r')
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except KeyboardInterrupt:
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print("\nInterrupted — saving partial export…")
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finally:
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decoder.release()
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# ── Write .txt ────────────────────────────────────────────────────────────
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header = (
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f"ASCILINE {mode_label} Export\n"
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f"cols={cols} rows={rows} fps={effective_fps:.3f} "
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f"frames={frame_idx} mode={mode_label.lower()}\n"
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f"{FRAME_SEP}\n"
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)
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with open(txt_path, "w", encoding="utf-8") as f:
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f.write(header)
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f.write(f"\n{FRAME_SEP}\n".join(txt_frames))
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print(f"\n✓ Saved {frame_idx} frames → {txt_path} ({os.path.getsize(txt_path)//1024} KB)")
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# ── Write .ascjson ───────────────────────────────────────────────────────
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if not no_color:
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meta = {
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"cols": cols,
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"rows": rows,
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"fps": round(effective_fps, 3),
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"mode": "pixel" if pixel_mode else "ascii",
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}
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with open(json_path, "w") as f:
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json.dump({"meta": meta, "frames": json_frames}, f, separators=(',', ':'))
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print(f"✓ Saved {frame_idx} frames → {json_path} ({os.path.getsize(json_path)//1024} KB)")
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# ── CLI ───────────────────────────────────────────────────────────────────────
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def main():
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ap = argparse.ArgumentParser(
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description="Export ASCILINE video to .txt and .ascjson",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Mode comparison:
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ASCII (default) — Character density + color, artistic look
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PIXEL (--pixel) — Solid █ blocks + 16M color RGB, ultra-high fidelity
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""")
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ap.add_argument("video", help="Path to video file")
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ap.add_argument("-o", "--output", default=None,
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help="Output file stem (default: same as video name)")
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ap.add_argument("--cols", type=int, default=240, help="ASCII columns (default 240, pixel 320)")
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ap.add_argument("--rows", type=int, default=None, help="ASCII rows (auto if omitted)")
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ap.add_argument("--max-fps", type=float, default=12, help="Cap output FPS (default 12)")
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ap.add_argument("--pixel", action="store_true",
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help="PIXEL mode: solid color blocks, 16M colors, ultra fidelity")
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ap.add_argument("--no-color", action="store_true", help="Skip .ascjson, txt only")
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ap.add_argument("--quiet", action="store_true", help="Suppress progress output")
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args = ap.parse_args()
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# Pixel mode defaults to higher resolution
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cols = args.cols
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if args.pixel and cols == 240:
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cols = 320 # pixel mode benefits from more columns
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stem = args.output or os.path.splitext(os.path.basename(args.video))[0]
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export(
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video_path = args.video,
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output_stem = stem,
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cols = cols,
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rows = args.rows,
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no_color = args.no_color,
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max_fps = args.max_fps,
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progress = not args.quiet,
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pixel_mode = args.pixel,
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)
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if __name__ == "__main__":
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main()
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final_viewr.html
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final_viewr.html
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requirements.txt
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requirements.txt
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fastapi
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uvicorn
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opencv-python
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numpy
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websockets
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