Fu DaiandClaude Opus 4.8
1a585693be
FastAPI service wrapping the Surya-OCR-2 model (datalab-to) served through vLLM: legacy /v1/api/ai/* endpoints, an OpenAI-compatible /v1/chat/completions endpoint, a coalescing request batcher, a local OCR CLI, Docker packaging, multilingual example outputs, and quantization/concurrency benchmarks. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
"""Post one or more images to an OCR endpoint and save text_lines per image.
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Used to freeze the accuracy baseline and to capture candidate outputs for CER.
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Usage:
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python scripts/capture_ocr_text.py \
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--url http://127.0.0.1:5002/v1/api/ai/suya_ocr_vllm/ \
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--out-dir baseline_outputs \
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temp_image_c3c56948-282e-453b-8fac-6c482243d1e5.jpg
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"""
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from __future__ import annotations
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import argparse
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import base64
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from pathlib import Path
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import requests
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def _payload(image_path: Path) -> dict:
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suffix = image_path.suffix.lstrip(".").lower() or "png"
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return {
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"file": base64.b64encode(image_path.read_bytes()).decode("utf-8"),
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"type": "jpg" if suffix == "jpeg" else suffix,
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"skip_text_detection": False,
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"skip_table_detection": False,
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"recognize_math": False,
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"ocr_with_boxes": True,
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}
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def capture(url: str, image_path: Path, out_dir: Path, timeout: float) -> str:
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resp = requests.post(url, json=_payload(image_path), timeout=timeout)
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body = resp.json()
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text = (body.get("data") or {}).get("text_lines", "") if isinstance(body.get("data"), dict) else ""
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out_dir.mkdir(parents=True, exist_ok=True)
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(out_dir / (image_path.stem + ".txt")).write_text(text, encoding="utf-8")
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return text
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def main() -> None:
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parser = argparse.ArgumentParser(description="Capture OCR text_lines per image.")
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parser.add_argument("images", nargs="+", type=Path)
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parser.add_argument("--url", required=True)
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parser.add_argument("--out-dir", type=Path, required=True)
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parser.add_argument("--timeout", type=float, default=900)
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args = parser.parse_args()
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for image in args.images:
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capture(args.url, image, args.out_dir, args.timeout)
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print(f"captured {image.name} -> {args.out_dir}")
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if __name__ == "__main__":
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main()
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