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.gitattributes

@@ -54,3 +54,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
 raw_formulas.jsonl filter=lfs diff=lfs merge=lfs -text
+common_formulas.jsonl filter=lfs diff=lfs merge=lfs -text

common_formulas.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:faa3cc98fb959a7dfd21d80393b32c45cea3f29811db2e231405aa70b538252c
+size 272368766

common_formulas.py

@@ -0,0 +1,107 @@
+from io import BytesIO
+from PIL import Image
+from pathlib import Path
+import datasets
+import json
+
+
+RAW_METADATA_URL = r'/home/lhy/arxiv_crawler/common_formulas/raw_formulas.jsonl'
+
+DIR_URL = r'/home/lhy/arxiv_crawler/common_formulas'
+
+
+class LatexFormulasConfig(datasets.BuilderConfig):
+    def __init__(self, data_url, **kwargs):
+        super().__init__(**kwargs)
+        self.data_url = data_url
+
+
+class LatexFormulas(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        LatexFormulasConfig(
+            name="raw_formulas",
+            data_url=RAW_METADATA_URL
+        ),
+        LatexFormulasConfig(
+            name="tokenized_formulas",
+            data_url=DIR_URL
+        )
+    ]
+
+    def _info(self):
+        if self.config.name == "raw_formulas":
+            return datasets.DatasetInfo(
+                features=datasets.Features({
+                    "latex_formula": datasets.Value("string")
+                })
+            )
+        if self.config.name == "tokenized_formulas":
+            return datasets.DatasetInfo(
+                features=datasets.Features({
+                    "image": datasets.Image(),
+                    "latex_formula": datasets.Value("string")
+                })
+            )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager):
+        data_path = dl_manager.download(self.config.data_url)
+        if self.config.name == 'raw_formulas':
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "data_path": data_path
+                    }
+                )
+            ]
+
+        if self.config.name == "tokenized_formulas":
+            dir_path = Path(data_path)
+            assert dir_path.is_dir()
+
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        'dir_path': dir_path,
+                        'dl_manager': dl_manager
+                    }
+                )
+            ]
+
+    def _generate_examples(self, data_path=None, dir_path: Path=None, dl_manager=None):
+        if self.config.name == 'tokenized_formulas':
+            idx = 0
+            for directory in dir_path.iterdir():
+                if not directory.is_dir():
+                    continue
+                if not directory.name.startswith('process'):
+                    continue
+                image_path = str(directory / "compressed_img.tar.gz")
+                metadata_path = str(directory / "tokenized_finally.jsonl")
+                images = dl_manager.iter_archive(image_path)
+
+                img_formula_pair = {}
+                with open(metadata_path, 'r', encoding='utf-8') as f:
+                    for line in f:
+                        single_json = json.loads(line)
+                        img_formula_pair[single_json['id']] = single_json['formula']
+
+                for img_path, img_obj in images:
+                    img_name = img_path.split('/')[-1]
+
+                    if img_name in img_formula_pair:
+                        idx += 1
+                        # yield idx, {
+                        yield str(directory) + img_path, {
+                            "image": {"path": img_path, "bytes": img_obj.read()},
+                            "latex_formula": img_formula_pair[img_name]
+                        }
+
+        if self.config.name == 'raw_formulas':
+            assert data_path is not None
+            with open(data_path, 'r', encoding="utf-8") as f:
+                for idx, line in enumerate(f):
+                    yield idx, {
+                        "latex_formula": json.loads(line)["formula"]
+                    }

process_0/compressed_img.tar.gz

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process_1/compressed_img.tar.gz

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process_5/compressed_img.tar.gz

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process_6/compressed_img.tar.gz

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process_7/compressed_img.tar.gz

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process_8/compressed_img.tar.gz

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process_9/compressed_img.tar.gz

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