first commit

json-split need to be checked

.gitattributes

@@ -52,3 +52,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,30 @@
 ---
-license: apache-2.0
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: token
+    dtype: string
+  - name: bounding_box
+    sequence:
+      sequence: uint16
+  - name: color
+    sequence:
+      sequence: uint8
+  - name: font
+    dtype: string
+  - name: label
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 17139
+    num_examples: 1
+  - name: validation
+    num_bytes: 17139
+    num_examples: 1
+  - name: test
+    num_bytes: 17139
+    num_examples: 1
+  download_size: 0
+  dataset_size: 51417
 ---

docbank.py

@@ -0,0 +1,167 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+
+"""DocBank document understanding dataset."""
+
+import os
+import datasets
+
+# Find for instance the citation on arxiv or on the dataset repo/website
+_CITATION = """\
+@misc{li2020docbank,
+    title={DocBank: A Benchmark Dataset for Document Layout Analysis},
+    author={Minghao Li and Yiheng Xu and Lei Cui and Shaohan Huang and Furu Wei and Zhoujun Li and Ming Zhou},
+    year={2020},
+    eprint={2006.01038},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """\
+DocBank is a new large-scale dataset that is constructed using a weak supervision approach. 
+It enables models to integrate both the textual and layout information for downstream tasks. 
+The current DocBank dataset totally includes 500K document pages, where 400K for training, 50K for validation and 50K for testing.
+"""
+
+_HOMEPAGE = "https://doc-analysis.github.io/docbank-page/index.html"
+
+_LICENSE = "Apache-2.0 license"
+
+
+class DocBank(datasets.GeneratorBasedBuilder):
+    """DocBank is a dataset for Visual Document Understanding. 
+    It enable models to integrate both textual and layout informtion for downstream tasks."""
+
+    VERSION = datasets.Version("1.1.0")    
+
+    @property
+    def manual_download_instructions(self):
+        return """\
+        Please download the DocBank dataset from https://doc-analysis.github.io/docbank-page/index.html. Uncompress the dataset and use that location in
+        --data_dir argument. """
+   
+    def _info(self):
+
+        features = datasets.Features(
+            {
+                "image": datasets.Image(),
+                "token": datasets.Value("string"),
+                "bounding_box": datasets.Sequence(datasets.Sequence(datasets.Value("uint16"))),
+                "color": datasets.Sequence(datasets.Sequence(datasets.Value("uint8"))),
+                "font": datasets.Value("string"),
+                "label": datasets.Value("string"),
+            }
+        )
+        
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # This defines the different columns of the dataset and their types
+            features=features,  # Here we define them above because they are different between the two configurations
+            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
+            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
+            # supervised_keys=("sentence", "label"),
+            # Homepage of the dataset for documentation
+            homepage=_HOMEPAGE,
+            # License for the dataset if available
+            license=_LICENSE,
+            # Citation for the dataset
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        # urls = _URLS[self.config.name]
+        # data_dir = dl_manager.download_and_extract(urls)
+        
+        self.data_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
+        
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join("train.jsonl"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join("dev.jsonl"),
+                    "split": "dev",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join("test.jsonl"),
+                    "split": "test"
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath, split):
+        
+        print(os.getcwd())
+        print(os.path.dirname(os.path.abspath(__file__)))
+        
+        with open(filepath,'rt') as fp:
+            index,basename = eval(fp.readline().strip())
+            
+            txt_file = self.data_dir+'/DocBank_500K_txt/'+basename+'.txt'
+            img_file = self.data_dir+'/DocBank_500K_ori_img/'+basename+'_ori.jpg'
+            
+            words = []
+            bboxes = []
+            rgbs = []
+            fontnames = []
+            structures = []
+
+            with open(txt_file, 'r', encoding='utf8') as fp:
+                for line in fp.readlines():
+                    tts = line.split('\t')
+                    
+                    assert len(tts) == 10, f'Incomplete line in file {txt_file}'
+
+                    word = tts[0]
+                    bbox = list(map(int, tts[1:5]))
+                    rgb = list(map(int, tts[5:8]))
+                    fontname = tts[8]
+                    structure = tts[9].strip()
+                    
+                    words.append(word)
+                    bboxes.append(bbox)
+                    rgbs.append(rgb)
+                    fontnames.append(fontname)
+                    structures.append(structure)            
+               
+        yield index, {
+            "image": img_file,
+            "token": words,
+            "bounding_box": bboxes,
+            "color": rgbs,
+            "font": fontnames,
+            "label": structures,
+        }

train.jsonl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a70200ff136876c3dea1d5b4430eea05cf40f4af0d08d160a642d2e893c5b7c7
+size 20655679