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Copy pathexample_ocr_numpy.py
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58 lines (44 loc) · 1.53 KB
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"""从 NumPy 数组进行 OCR 识别示例。"""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
import numpy as np
import liteocr
def main(argv: list[str] | None = None) -> int:
parser = argparse.ArgumentParser(description="LiteOCR NumPy 数组识别示例")
parser.add_argument(
"image",
nargs="?",
default="test.png",
help="待识别图片路径(默认:test.png)",
)
parser.add_argument(
"--preset",
default="PP-OCRv5_mobile",
help="使用的 OCR 预设(默认:PP-OCRv5_mobile)",
)
parser.add_argument(
"--model-dir",
default="models",
help="模型文件存放目录(默认:models)",
)
args = parser.parse_args(argv)
image_path = Path(args.image)
if not image_path.exists():
print(f"图片不存在:{image_path}", file=sys.stderr)
return 1
# 用 Pillow 或 opencv 读取均可,这里用 LiteOCR 自带接口读取后再转 NumPy。
img = liteocr.load_image(str(image_path))
arr = img.to_numpy()
print(f"图片数组 shape:{arr.shape}, dtype:{arr.dtype}")
engine = liteocr.Engine()
engine.load_preset(args.preset, model_dir=args.model_dir)
print("从 NumPy 数组识别...")
result = engine.recognize(arr)
print(f"\n识别结果(共 {len(result.lines)} 行):")
for i, line in enumerate(result.lines, 1):
print(f"{i}. {line.text}")
return 0
if __name__ == "__main__":
sys.exit(main())