PaddleOCR/ppocr/utils/formula_utils/math_txt2pkl.py

75 lines
2.5 KiB
Python

# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import pickle
from tqdm import tqdm
import os
import math
from paddle.utils import try_import
from collections import defaultdict
import glob
from os.path import join
import argparse
def txt2pickle(images, equations, save_dir):
imagesize = try_import("imagesize")
save_p = os.path.join(save_dir, "latexocr_{}.pkl".format(images.split("/")[-1]))
min_dimensions = (32, 32)
max_dimensions = (672, 192)
max_length = 512
data = defaultdict(lambda: [])
if images is not None and equations is not None:
images_list = [
path.replace("\\", "/") for path in glob.glob(join(images, "*.png"))
]
indices = [int(os.path.basename(img).split(".")[0]) for img in images_list]
eqs = open(equations, "r").read().split("\n")
for i, im in tqdm(enumerate(images_list), total=len(images_list)):
width, height = imagesize.get(im)
if (
min_dimensions[0] <= width <= max_dimensions[0]
and min_dimensions[1] <= height <= max_dimensions[1]
):
divide_h = math.ceil(height / 16) * 16
divide_w = math.ceil(width / 16) * 16
im = os.path.basename(im)
data[(divide_w, divide_h)].append((eqs[indices[i]], im))
data = dict(data)
with open(save_p, "wb") as file:
pickle.dump(data, file)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--image_dir",
type=str,
default=".",
help="Input_label or input path to be converted",
)
parser.add_argument(
"--mathtxt_path",
type=str,
default=".",
help="Input_label or input path to be converted",
)
parser.add_argument(
"--output_dir", type=str, default="out_label.txt", help="Output file name"
)
args = parser.parse_args()
txt2pickle(args.image_dir, args.mathtxt_path, args.output_dir)