Split project into frontend and backend

2026-08-13 16:24:36 +08:00
commit f051146486
274 changed files with 953932 additions and 0 deletions
@@ -0,0 +1,127 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import os
+import re
+import subprocess
+import sys
+from pathlib import Path
+
+
+SWIFT_CODE = r'''
+import Foundation
+import Vision
+import AppKit
+
+let path = CommandLine.arguments[1]
+let url = URL(fileURLWithPath: path)
+guard let img = NSImage(contentsOf: url),
+      let tiff = img.tiffRepresentation,
+      let bitmap = NSBitmapImageRep(data: tiff),
+      let cg = bitmap.cgImage else {
+    fputs("image load failed\n", stderr)
+    exit(3)
+}
+
+struct Line {
+    let text: String
+    let x: CGFloat
+    let y: CGFloat
+}
+
+var lines: [Line] = []
+var requestError: Error?
+let request = VNRecognizeTextRequest { req, err in
+    if let err = err {
+        requestError = err
+        return
+    }
+    let observations = (req.results as? [VNRecognizedTextObservation]) ?? []
+    lines = observations.compactMap { observation in
+        guard let candidate = observation.topCandidates(1).first else { return nil }
+        let text = candidate.string.trimmingCharacters(in: .whitespacesAndNewlines)
+        guard !text.isEmpty else { return nil }
+        return Line(text: text, x: observation.boundingBox.minX, y: observation.boundingBox.maxY)
+    }
+}
+request.recognitionLevel = .accurate
+request.usesLanguageCorrection = true
+request.recognitionLanguages = ["zh-Hans", "en-US"]
+
+let handler = VNImageRequestHandler(cgImage: cg, options: [:])
+do {
+    try handler.perform([request])
+} catch {
+    fputs("\(error.localizedDescription)\n", stderr)
+    exit(4)
+}
+if let requestError = requestError {
+    fputs("\(requestError.localizedDescription)\n", stderr)
+    exit(5)
+}
+
+let sorted = lines.sorted {
+    if abs($0.y - $1.y) > 0.012 {
+        return $0.y > $1.y
+    }
+    return $0.x < $1.x
+}
+for line in sorted {
+    print(line.text)
+}
+'''
+
+
+def page_number(path: Path) -> int:
+    match = re.search(r"(\d+)", path.stem)
+    return int(match.group(1)) if match else 0
+
+
+def run_ocr(image: Path, module_cache: Path) -> tuple[str, str | None]:
+    module_cache.mkdir(parents=True, exist_ok=True)
+    env = os.environ.copy()
+    env["CLANG_MODULE_CACHE_PATH"] = str(module_cache)
+    proc = subprocess.run(
+        ["swift", "-e", SWIFT_CODE, str(image)],
+        text=True,
+        capture_output=True,
+        check=False,
+        env=env,
+    )
+    if proc.returncode != 0:
+        return "", proc.stderr.strip() or f"swift exited {proc.returncode}"
+    return proc.stdout.strip(), None
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("output", type=Path)
+    parser.add_argument("images", nargs="+", type=Path)
+    args = parser.parse_args()
+
+    images = sorted(args.images, key=lambda p: (page_number(p), str(p)))
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    module_cache = args.output.parent.parent / "tmp" / "swift_module_cache"
+
+    with args.output.open("w", encoding="utf-8") as out:
+        out.write("# GB/T 33923-2017 OCR 文本版\n\n")
+        out.write("> 说明：此文本由 PDF 页面图像 OCR 生成，用于阅读、搜索和复制。公式、表格、上下标和个别专业符号可能需要对照原 PDF 校核。\n\n")
+        for index, image in enumerate(images, 1):
+            page = page_number(image)
+            print(f"OCR page {index}/{len(images)}: {image.name}", file=sys.stderr, flush=True)
+            text, error = run_ocr(image, module_cache)
+            out.write(f"\n\n## 第 {page} 页\n\n")
+            if error:
+                out.write(f"[OCR 失败：{error}]\n")
+            elif text:
+                out.write(text)
+                out.write("\n")
+            else:
+                out.write("[OCR 未识别出文本]\n")
+            out.flush()
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())