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85 lines
2.7 KiB
85 lines
2.7 KiB
1 month ago
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#!/usr/bin/env python3
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"""
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PaddleOCR E2EMetric (mode: A)이 요구하는 gt_img_{N}.mat 파일을 생성.
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입력: PGDataSet 포맷의 label txt 파일
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images/000000.jpg\t[{"transcription":"37도1563","points":[[x1,y1],...]}]
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출력: gt_mat_dir/gt_img_{1-indexed}.mat (ICDAR2015 wordBB 포맷)
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사용법 (서버에서):
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python3.10 /workspace/kr_lp_pgnet/tools/make_gt_mat.py \
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--label /workspace/train_data/kr_lp_synth/test/test.txt \
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--out_dir /workspace/train_data/kr_lp_synth/gt
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"""
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import argparse
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import json
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import os
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import numpy as np
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import scipy.io as sio
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def points_to_wordbb(points):
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"""[[x0,y0],[x1,y1],[x2,y2],[x3,y3]] → (2, 4) array (ICDAR wordBB 포맷).
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axis0: x or y, axis1: corner index (TL, TR, BR, BL)."""
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pts = np.array(points, dtype=np.float64) # (4, 2)
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# (2, 4): row0=x coords, row1=y coords
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return pts.T # [[x0..x3], [y0..y3]]
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def make_txt_cell(text):
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"""ICDAR txt 셀: numpy array of individual chars (MATLAB cell array 호환)."""
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return np.array([list(text)], dtype=object)
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def main():
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p = argparse.ArgumentParser(description=__doc__)
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p.add_argument("--label", required=True, help="PGDataSet label txt 경로")
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p.add_argument("--out_dir", required=True, help="gt mat 출력 디렉토리")
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args = p.parse_args()
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os.makedirs(args.out_dir, exist_ok=True)
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with open(args.label, encoding="utf-8") as f:
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lines = [ln.rstrip("\n") for ln in f if ln.strip()]
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for img_idx, line in enumerate(lines, start=1):
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parts = line.split("\t", 1)
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if len(parts) != 2:
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print(f" skip (no tab): {line[:60]}")
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continue
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try:
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entries = json.loads(parts[1])
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except json.JSONDecodeError as ex:
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print(f" skip (json err @ {img_idx}): {ex}")
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continue
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n = len(entries)
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if n == 0:
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print(f" skip (empty label @ {img_idx})")
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continue
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# wordBB: (2, 4, N) — ICDAR 포맷
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word_bb = np.zeros((2, 4, n), dtype=np.float64)
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txt = np.empty((1, n), dtype=object)
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for j, entry in enumerate(entries):
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word_bb[:, :, j] = points_to_wordbb(entry["points"])
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txt[0, j] = make_txt_cell(entry["transcription"])
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if n == 1:
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# scipy.io는 (2,4,1) → (2,4)로 squeeze하는 경우가 있어 명시적 유지
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word_bb = word_bb.reshape(2, 4, 1)
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mat_path = os.path.join(args.out_dir, f"gt_img_{img_idx}.mat")
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sio.savemat(mat_path, {"wordBB": word_bb, "txt": txt}, do_compression=True)
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print(f" gt mat 생성 완료: {len(lines)}개 → {args.out_dir}/gt_img_{{1..{len(lines)}}}.mat")
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if __name__ == "__main__":
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main()
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