Download pdf2png.py from divinity-library/scripts: direct link, hf CLI and curl.
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https://huggingface.co/datasets/divinity-library/scripts/resolve/main/pdf2png.py
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hf download hf://datasets/divinity-library/scripts/pdf2png.py
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curl -L -o pdf2png.py https://huggingface.co/datasets/divinity-library/scripts/resolve/main/pdf2png.py
8.3 kB
| # /// script | |
| # requires-python = ">=3.10" | |
| # dependencies = ["pypdfium2>=4.30", "pillow>=10", "pyarrow>=15", "huggingface-hub>=1.0"] | |
| # /// | |
| r"""Render every page of every PDF under INPUT to PNG, saved either as files in a | |
| folder or as a Hugging Face dataset with one row per page: | |
| OUTPUT ./pages -> pages/1850s/vol1/page-0001.png, page-0002.png, ... | |
| OUTPUT hf://datasets/USER/X -> rows of (image, pdf, page) in Parquet, one file per PDF: | |
| data/1850s/vol1.parquet, ... | |
| PDFs finished on an earlier run are skipped either way, so a run that stops | |
| partway (e.g. a job hitting its timeout) can simply be started again. | |
| uv run pdf2png.py ./pdfs ./pages | |
| hf jobs uv run --flavor cpu-upgrade --timeout 3h -s HF_TOKEN -v hf://datasets/USER/pdfs:/in \ | |
| -- https://huggingface.co/datasets/USER/scripts/resolve/main/pdf2png.py /in hf://datasets/USER/pages | |
| """ | |
| import argparse | |
| import io | |
| import json | |
| import os | |
| import sys | |
| import tempfile | |
| from concurrent.futures import ProcessPoolExecutor, as_completed | |
| from pathlib import Path | |
| import pyarrow as pa | |
| import pyarrow.parquet as pq | |
| import pypdfium2 as pdfium | |
| from huggingface_hub import CommitOperationAdd, HfApi | |
| from huggingface_hub.utils import disable_progress_bars | |
| DONE = ".done" # folder output: written into a PDF's folder once all of its pages are saved | |
| COMMIT_FILES, COMMIT_BYTES = 50, 5 * 10**9 # dataset output: commit every 50 PDFs or 5 GB, whichever comes first | |
| ROW_GROUP_BYTES = 100 * 10**6 # keeps Parquet row groups small enough for the dataset viewer | |
| FEATURES = {"image": {"_type": "Image"}, "pdf": {"dtype": "string", "_type": "Value"}, | |
| "page": {"dtype": "int32", "_type": "Value"}} | |
| SCHEMA = pa.schema( | |
| [("image", pa.struct([("bytes", pa.binary()), ("path", pa.string())])), ("pdf", pa.string()), ("page", pa.int32())], | |
| metadata={"huggingface": json.dumps({"info": {"features": FEATURES}})}, # so `image` loads as images | |
| ) | |
| README = """--- | |
| configs: | |
| - config_name: default | |
| data_files: "data/**/*.parquet" | |
| --- | |
| Pages rendered from PDFs with pdf2png.py: one row per page, with `image` (PNG), `pdf` and `page` columns. | |
| """ | |
| def render(pdf_path: Path, dpi: int, grayscale: bool): | |
| """Yield (filename, PNG bytes) for each page of a PDF.""" | |
| pdf = pdfium.PdfDocument(pdf_path) | |
| try: | |
| pdf.init_forms() # so filled-in form fields render as they do in a viewer | |
| n = len(pdf) | |
| for i in range(n): | |
| page = pdf[i] | |
| buf = io.BytesIO() | |
| # still lossless; ~3x faster than the default level on scans, files ~10% larger | |
| page.render(scale=dpi / 72, grayscale=grayscale).to_pil().save(buf, "PNG", compress_level=1) | |
| page.close() | |
| yield f"page-{i + 1:0{max(4, len(str(n)))}d}.png", buf.getvalue() | |
| finally: | |
| pdf.close() | |
| def to_folder(pdf_path: Path, out_dir: Path, dpi: int, grayscale: bool) -> int: | |
| out_dir.mkdir(parents=True, exist_ok=True) | |
| n = 0 | |
| for n, (filename, png) in enumerate(render(pdf_path, dpi, grayscale), 1): | |
| (out_dir / filename).write_bytes(png) | |
| (out_dir / DONE).touch() | |
| return n | |
| def to_parquet(pdf_path: Path, out_file: Path, name: str, dpi: int, grayscale: bool) -> int: | |
| out_file.parent.mkdir(parents=True, exist_ok=True) | |
| stem = Path(name).with_suffix("").as_posix() | |
| rows, size, n = [], 0, 0 | |
| with pq.ParquetWriter(out_file, SCHEMA) as writer: | |
| for n, (filename, png) in enumerate(render(pdf_path, dpi, grayscale), 1): | |
| rows.append({"image": {"bytes": png, "path": f"{stem}/{filename}"}, "pdf": name, "page": n}) | |
| size += len(png) | |
| if size >= ROW_GROUP_BYTES: | |
| writer.write_table(pa.Table.from_pylist(rows, SCHEMA)) | |
| rows, size = [], 0 | |
| if rows: | |
| writer.write_table(pa.Table.from_pylist(rows, SCHEMA)) | |
| return n | |
| def push(api: HfApi, repo: str, staging: Path, files: list) -> None: | |
| """Commit finished Parquet files to the dataset repo, then delete the local copies.""" | |
| if files: | |
| ops = [CommitOperationAdd(path_in_repo=f.relative_to(staging).as_posix(), path_or_fileobj=f) for f in files] | |
| api.create_commit(repo, ops, commit_message=f"Add {len(files)} PDFs", repo_type="dataset") | |
| print(f"committed {len(files)} PDFs to {repo}", flush=True) | |
| for f in files: | |
| f.unlink() | |
| files.clear() | |
| def main() -> None: | |
| parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) | |
| parser.add_argument("input", type=Path, help="folder of PDFs (searched recursively), or a single PDF") | |
| parser.add_argument("output", help="folder for the PNGs, or hf://datasets/USER/NAME for a dataset") | |
| parser.add_argument("--dpi", type=int, default=300, help="render resolution (default: 300)") | |
| parser.add_argument("--grayscale", action="store_true", help="8-bit grayscale PNGs: smaller files, faster") | |
| parser.add_argument("--private", action="store_true", help="make the dataset repo private, if it gets created") | |
| parser.add_argument("--workers", type=int, default=int(os.environ.get("CPU_CORES") or os.cpu_count() or 1), | |
| help="parallel processes (default: one per CPU core)") | |
| args = parser.parse_args() | |
| if args.input.is_file(): | |
| root, pdfs = args.input.parent, [args.input] | |
| else: | |
| root = args.input | |
| pdfs = sorted(p for p in root.rglob("*") if p.suffix.lower() == ".pdf" and p.is_file()) | |
| names = {pdf: pdf.relative_to(root).as_posix() for pdf in pdfs} | |
| stems = {pdf: pdf.relative_to(root).with_suffix("").as_posix() for pdf in pdfs} | |
| todo = {} # pdf -> (worker, *args) | |
| repo = args.output.removeprefix("hf://datasets/").strip("/") if args.output.startswith("hf://datasets/") else None | |
| if repo: | |
| disable_progress_bars() | |
| api = HfApi() # authenticates with HF_TOKEN (pass it to a job with -s HF_TOKEN) | |
| api.create_repo(repo, repo_type="dataset", private=args.private or None, exist_ok=True) | |
| existing = set(api.list_repo_files(repo, repo_type="dataset")) | |
| if "README.md" not in existing: | |
| api.upload_file(path_or_fileobj=README.encode(), path_in_repo="README.md", repo_id=repo, | |
| repo_type="dataset", commit_message="Add dataset card") | |
| tmp = tempfile.TemporaryDirectory(prefix="pdf2png-") # removed when the script exits | |
| staging = Path(tmp.name) | |
| for pdf in pdfs: | |
| target = f"data/{stems[pdf]}.parquet" | |
| if target not in existing: | |
| todo[pdf] = (to_parquet, pdf, staging / target, names[pdf], args.dpi, args.grayscale) | |
| else: | |
| for pdf in pdfs: | |
| out_dir = Path(args.output, stems[pdf]) | |
| if not (out_dir / DONE).exists(): | |
| todo[pdf] = (to_folder, pdf, out_dir, args.dpi, args.grayscale) | |
| print(f"{len(pdfs)} PDFs found, {len(pdfs) - len(todo)} already done, {len(todo)} to convert", flush=True) | |
| if not todo: | |
| return | |
| failed, pending = [], [] | |
| with ProcessPoolExecutor(min(args.workers, len(todo))) as pool: | |
| futures = {pool.submit(*job): pdf for pdf, job in todo.items()} | |
| try: | |
| for i, future in enumerate(as_completed(futures), 1): | |
| pdf = futures[future] | |
| try: | |
| n = future.result() | |
| except Exception as e: | |
| failed.append(names[pdf]) | |
| print(f"[{i}/{len(todo)}] {names[pdf]}: FAILED ({e})", flush=True) | |
| continue | |
| print(f"[{i}/{len(todo)}] {names[pdf]}: {n} pages", flush=True) | |
| if repo: | |
| pending.append(todo[pdf][2]) | |
| if len(pending) >= COMMIT_FILES or sum(f.stat().st_size for f in pending) >= COMMIT_BYTES: | |
| push(api, repo, staging, pending) | |
| if repo: | |
| push(api, repo, staging, pending) | |
| except BaseException: | |
| pool.shutdown(cancel_futures=True) # stop rendering PDFs whose output can't be saved | |
| raise | |
| if failed: | |
| sys.exit(f"{len(failed)} PDF(s) failed: {', '.join(failed)}") | |
| if __name__ == "__main__": | |
| main() | |