Upload ONNX export

fetch_example_images.py

@@ -0,0 +1,105 @@
+"""Fetch open-source document images with dense, varied layouts for the model card gallery.
+
+Pulls sample pages from the CDLA-Permissive-1.0-licensed `creative-graphic-design/PubLayNet`
+dataset on the Hugging Face Hub (a re-hosting of PubLayNet: Zhong et al., 2019,
+https://arxiv.org/abs/1908.07836 — scientific articles from PubMed Central Open Access).
+Scores a scan window of rows by their COCO-annotation count (a proxy for layout density —
+how many text/title/list/table/figure regions are on the page) and downloads the densest ones,
+so the gallery shows the model handling as many layout elements as possible per image.
+
+Uses only the HF `datasets-server` `/rows` REST API (plain paginated JSON + signed image URLs)
+— no `datasets`/torch/pyarrow dependency needed.
+
+Usage:
+    python fetch_example_images.py --count 5 --scan 3000 --out-dir examples/inputs
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import urllib.request
+from pathlib import Path
+
+DATASET = "creative-graphic-design/PubLayNet"
+ROWS_URL = "https://datasets-server.huggingface.co/rows"
+PAGE = 100
+
+
+def scan(scan_rows: int, split: str) -> list[dict]:
+    candidates = []
+    for offset in range(0, scan_rows, PAGE):
+        url = (
+            f"{ROWS_URL}?dataset={DATASET.replace('/', '%2F')}&config=default"
+            f"&split={split}&offset={offset}&length={PAGE}"
+        )
+        try:
+            with urllib.request.urlopen(url, timeout=30) as r:
+                payload = json.load(r)
+        except Exception as exc:
+            print(f"  offset {offset}: skipped ({exc})")
+            continue
+        for item in payload["rows"]:
+            row = item["row"]
+            candidates.append(
+                {
+                    "file_name": row["file_name"],
+                    "width": row["width"],
+                    "height": row["height"],
+                    "n_boxes": len(row["annotations"]["bbox"]),
+                    "n_classes": len(set(row["annotations"]["category_id"])),
+                    "src": row["image"]["src"],
+                }
+            )
+        print(f"  offset {offset}: scanned ({len(candidates)} candidates so far)")
+    return candidates
+
+
+def main() -> int:
+    p = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
+    p.add_argument("--count", type=int, default=5, help="how many images to download")
+    p.add_argument("--scan", type=int, default=2000, help="how many dataset rows to scan for density")
+    p.add_argument("--split", default="train")
+    p.add_argument("--out-dir", type=Path, default=Path("examples/inputs"))
+    args = p.parse_args()
+
+    args.out_dir.mkdir(parents=True, exist_ok=True)
+    print(f"Scanning {args.scan} rows of {DATASET} ({args.split}) for the densest layouts...")
+    candidates = scan(args.scan, args.split)
+    if not candidates:
+        raise SystemExit("no candidates found — dataset-server may be unreachable")
+
+    candidates.sort(key=lambda c: (-c["n_boxes"], -c["n_classes"]))
+    chosen = candidates[: args.count]
+
+    manifest = []
+    print("\nDownloading:")
+    for c in chosen:
+        dest = args.out_dir / c["file_name"]
+        urllib.request.urlretrieve(c["src"], dest)
+        print(f"  {c['n_boxes']:3d} boxes, {c['n_classes']} classes -> {dest.name} ({c['width']}x{c['height']})")
+        manifest.append({k: v for k, v in c.items() if k != "src"})
+
+    (args.out_dir / "SOURCE.json").write_text(
+        json.dumps(
+            {
+                "dataset": DATASET,
+                "dataset_url": f"https://huggingface.co/datasets/{DATASET}",
+                "license": "CDLA-Permissive-1.0",
+                "citation": (
+                    "Zhong, X., Tang, J., & Yepes, A. J. (2019). "
+                    "PubLayNet: largest dataset ever for document layout analysis. "
+                    "arXiv:1908.07836"
+                ),
+                "note": "Pages sourced from PubMed Central open-access scientific articles.",
+                "images": manifest,
+            },
+            indent=2,
+        )
+    )
+    print(f"\n{len(chosen)} image(s) -> {args.out_dir}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())