scripts/onnx_ocr.py

#!/usr/bin/env python3
"""用训练好的位置保留模型识别验证码。输出格式兼容 harness。
预处理: 灰度->开运算去噪->RGB 160x64 /255 -> (1,3,64,160) -> (1,4,10) -> 4位数字
"""
import json
import os
import sys

import cv2
import numpy as np
import onnxruntime as ort
from PIL import Image

MODEL = os.path.expanduser("~/sp_captcha_assets/models/captcha_1000.onnx")
_sess = None


def _get_sess():
    global _sess
    if _sess is None:
        _sess = ort.InferenceSession(MODEL, providers=["CPUExecutionProvider"])
    return _sess


def predict(path):
    img = cv2.imread(path, cv2.IMREAD_GRAYSCALE)
    k = np.ones((2, 2), np.uint8)
    denoised = cv2.morphologyEx(img, cv2.MORPH_OPEN, k)
    im = Image.fromarray(denoised).convert("RGB").resize((160, 64), Image.BILINEAR)
    a = np.asarray(im, dtype=np.float32) / 255.0
    x = a.transpose(2, 0, 1)[None]  # (1,3,64,160)
    out = _get_sess().run(None, {"input": x})[0]  # (1,4,10)
    return "".join(str(int(out[0, p].argmax())) for p in range(4))


def main():
    out = {}
    for f in sys.argv[1:]:
        try:
            out[f] = {"onnx": predict(f)}
        except Exception as e:
            out[f] = {"onnx": "", "err": str(e)}
    print(json.dumps(out, ensure_ascii=False))


if __name__ == "__main__":
    main()