Datasets:
Tasks:
Document Question Answering
Size:
n<1K
Tags:
benchmark
document-ai
information-extraction
structured-extraction
key-information-extraction
ocr
License:
| #!/usr/bin/env python3 | |
| """generate downscaled page images + docupipe extraction json for the landing-page benchmark modal.""" | |
| import json, os, re, subprocess, glob, tempfile | |
| ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) | |
| OUT = "/Users/urimerhav/Code/docupanda-website/public/benchmarks/docs" | |
| MAX_PAGES = 5 | |
| WIDTH = 1000 | |
| html = open(os.path.join(ROOT, "docubench-explorer.html"), encoding="utf-8").read() | |
| DATA = json.loads(re.search(r"const DATA = (\{.*?\});", html, re.S).group(1)) | |
| DOCS = {d["id"]: d for d in DATA["docs"]} | |
| ids = json.load(open("/tmp/dbids.json")) | |
| os.makedirs(OUT, exist_ok=True) | |
| def sips_to_jpeg(src, dst): | |
| subprocess.run(["sips", "-s", "format", "jpeg", "-s", "formatOptions", "72", | |
| "-Z", str(WIDTH), src, "--out", dst], | |
| stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) | |
| def render_pdf(path, outdir): | |
| with tempfile.TemporaryDirectory() as td: | |
| prefix = os.path.join(td, "pg") | |
| subprocess.run(["pdftoppm", "-jpeg", "-r", "110", "-f", "1", "-l", str(MAX_PAGES), path, prefix], | |
| stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) | |
| pages = sorted(glob.glob(prefix + "*")) | |
| for i, p in enumerate(pages, 1): | |
| sips_to_jpeg(p, os.path.join(outdir, f"p{i}.jpg")) | |
| return len(pages) | |
| def render_image(path, outdir): | |
| sips_to_jpeg(path, os.path.join(outdir, "p1.jpg")) | |
| return 1 | |
| def render_quicklook(path, outdir): | |
| with tempfile.TemporaryDirectory() as td: | |
| subprocess.run(["qlmanage", "-t", "-s", "1300", "-o", td, path], | |
| stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) | |
| pngs = glob.glob(os.path.join(td, "*.png")) | |
| if not pngs: | |
| return 0 | |
| sips_to_jpeg(pngs[0], os.path.join(outdir, "p1.jpg")) | |
| return 1 | |
| manifest = {} | |
| for did in ids: | |
| doc = DOCS[did] | |
| ext = doc["ftype"] | |
| src = glob.glob(os.path.join(ROOT, "documents", did + ".*")) | |
| if not src: | |
| print("MISSING doc", did); continue | |
| src = src[0] | |
| outdir = os.path.join(OUT, did) | |
| os.makedirs(outdir, exist_ok=True) | |
| if ext == "pdf": | |
| n = render_pdf(src, outdir) | |
| elif ext in ("jpeg", "jpg", "png", "tiff", "tif"): | |
| n = render_image(src, outdir) | |
| else: # csv, xlsx, docx, xml, txt, html | |
| n = render_quicklook(src, outdir) | |
| # docupipe high-effort extraction json -> standardization.json (just the data object) | |
| res_path = os.path.join(ROOT, "results", "docupipe_high", did + ".json") | |
| res = json.load(open(res_path, encoding="utf-8")) | |
| json.dump(res.get("data", {}), open(os.path.join(outdir, "standardization.json"), "w", encoding="utf-8"), | |
| ensure_ascii=False) | |
| manifest[did] = { | |
| "pages": n, | |
| "ftype": ext, | |
| "origPages": doc["pages"], | |
| "score": round(res.get("score", 0), 4), | |
| } | |
| print(f"{did}: {ext:5s} pages={n} origPages={doc['pages']}") | |
| json.dump(manifest, open(os.path.join(OUT, "manifest.json"), "w"), indent=0) | |
| print("\nmanifest written:", len(manifest), "docs ->", OUT) | |