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123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134#!/usr/bin/env python3"""ocr_pipeline.py — Capture framebuffer region → OCR → return text
Usage: python ocr_pipeline.py [--region x,y,w,h] [--output text.txt]
Captures the reMarkable framebuffer via SSH, crops to the specified region,runs PaddleOCR, and prints/saves the recognized text."""
import argparseimport subprocessimport tempfileimport structfrom pathlib import Path
# Framebuffer constants for rM2FB_WIDTH = 1404FB_HEIGHT = 1872FB_BPP = 4 # RGBAFB_DEVICE = "/dev/fb0"
def capture_framebuffer(region=None): """Capture framebuffer from device via SSH, return as raw bytes.""" if region: x, y, w, h = region # Use dd to capture only the needed rows, then crop columns cmd = f"dd if={FB_DEVICE} bs={FB_WIDTH * FB_BPP} skip={y} count={h} 2>/dev/null" else: cmd = f"cat {FB_DEVICE}" result = subprocess.run( ["ssh", "remarkable", cmd], capture_output=True, timeout=10 ) if result.returncode != 0: raise RuntimeError(f"Failed to capture framebuffer: {result.stderr.decode()}") raw = result.stdout if region: x, y, w, h = region # Crop columns from each row cropped = b"" row_size = FB_WIDTH * FB_BPP for row_y in range(h): row_start = row_y * row_size + x * FB_BPP cropped += raw[row_start:row_start + w * FB_BPP] return cropped, w, h else: return raw, FB_WIDTH, FB_HEIGHT
def raw_to_image(raw_bytes, width, height): """Convert raw framebuffer bytes to PIL Image.""" from PIL import Image # rM2 framebuffer is BGR (not RGBA), 32bpp but only 24 bits used # Try BGR first, fall back to RGBA try: img = Image.frombytes("RGB", (width, height), raw_bytes, "raw", "BGR") except Exception: img = Image.frombytes("RGBA", (width, height), raw_bytes) img = img.convert("RGB") # E-ink displays often have inverted or low-contrast content # Auto-enhance contrast for better OCR from PIL import ImageEnhance enhancer = ImageEnhance.Contrast(img) img = enhancer.enhance(3.0) return img
def ocr_image(image): """Run PaddleOCR on a PIL Image, return recognized text.""" from paddleocr import PaddleOCR ocr = PaddleOCR(use_textline_orientation=True, lang="en") # Save to temp file for PaddleOCR with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as f: image.save(f.name) result = ocr.predict(f.name) # Extract text from results texts = [] for item in result: if hasattr(item, 'rec_texts'): texts.extend(item.rec_texts) elif isinstance(item, dict) and 'rec_texts' in item: texts.extend(item['rec_texts']) return " ".join(texts)
def main(): parser = argparse.ArgumentParser(description="OCR pipeline for reMarkable") parser.add_argument("--region", type=str, default=None, help="Crop region as x,y,w,h (pixels)") parser.add_argument("--output", type=str, default=None, help="Save recognized text to file") parser.add_argument("--image", type=str, default=None, help="Use local image instead of capturing framebuffer") args = parser.parse_args() if args.image: from PIL import Image img = Image.open(args.image).convert("RGB") text = ocr_image(img) else: region = None if args.region: region = tuple(int(x) for x in args.region.split(",")) print(f"Capturing framebuffer (region={region})...") raw, w, h = capture_framebuffer(region) print(f"Captured {w}x{h} ({len(raw)} bytes)") img = raw_to_image(raw, w, h) text = ocr_image(img) print(f"Recognized text: {text}") if args.output: Path(args.output).write_text(text) print(f"Saved to {args.output}")
if __name__ == "__main__": main()