diff --git a/Datasets/dataset_formatters/extract_from_arkindex.py b/Datasets/dataset_formatters/extract_from_arkindex.py
deleted file mode 100644
index fe1d24f4d7d591526bac5102e5fcbe0184658281..0000000000000000000000000000000000000000
--- a/Datasets/dataset_formatters/extract_from_arkindex.py
+++ /dev/null
@@ -1,170 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-#
-# Example of minimal usage:
-# python extract_from_arkindex.py
-# --corpus "AN-Simara annotations E (2022-06-20)"
-# --parents-types folder
-# --parents-names FRAN_IR_032031_4538.pdf
-# --output-dir ../
-
-"""
- The extraction module
- ======================
-"""
-
-import logging
-import os
-from re import S
-
-import imageio.v2 as iio
-from arkindex import ArkindexClient, options_from_env
-from tqdm import tqdm
-
-from extraction_utils import arkindex_utils as ark
-from extraction_utils import utils
-from utils_dataset import assign_random_split, save_text, save_image, save_json
-
-logging.basicConfig(
- level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
-)
-
-
-IMAGES_DIR = "./images/" # Path to the images directory.
-LABELS_DIR = "./labels/" # Path to the labels directory.
-
-
-# Layout string to token
-SEM_MATCHING_TOKENS_STR = {
- "INTITULE": "ⓘ",
- "DATE": "â““",
- "COTE_SERIE": "â“¢",
- "ANALYSE_COMPL.": "â“’",
- "PRECISIONS_SUR_COTE": "â“Ÿ",
- "COTE_ARTICLE": "â“"
-}
-
-# Layout begin-token to end-token
-SEM_MATCHING_TOKENS = {
- "ⓘ": "Ⓘ",
- "â““": "â’¹",
- "ⓢ": "Ⓢ",
- "â“’": "â’¸",
- "â“Ÿ": "â“…",
- "â“": "â’¶"
-}
-
-
-def extract_transcription(element, no_entities=False):
- tr = client.request('ListTranscriptions', id=element['id'], worker_version=None)['results']
- tr = [one for one in tr if one['worker_version_id'] is None]
-
- if len(tr) != 1:
- return None
-
- if no_entities:
- text = tr[0]['text'].strip()
-
- else:
- for one_tr in tr:
- ent = client.request('ListTranscriptionEntities', id=one_tr['id'])['results']
- print(ent)
- ent = [one for one in ent if one['worker_version_id'] is None]
- if len(ent) == 0:
- continue
- else:
- text = one_tr['text']
-
- count = 0
- for e in ent:
- start_token = SEM_MATCHING_TOKENS_STR[e['entity']['metas']['subtype']]
- end_token = SEM_MATCHING_TOKENS[start_token]
- text = text[:count+e['offset']] + start_token + text[count+e['offset']:]
- count += 1
- text = text[:count+e['offset']+e['length']] + end_token + text[count+e['offset']+e['length']:]
- count += 1
- return text
-
-
-if __name__ == '__main__':
- args = utils.get_cli_args()
-
- # Get and initialize the parameters.
- os.makedirs(IMAGES_DIR, exist_ok=True)
- os.makedirs(LABELS_DIR, exist_ok=True)
-
- # Login to arkindex.
- client = ArkindexClient(**options_from_env())
- corpus = ark.retrieve_corpus(client, args.corpus)
- subsets = ark.retrieve_subsets(
- client, corpus, args.parents_types, args.parents_names
- )
-
- # Create out directories
- split_dict = {}
- split_names = [subset["name"] for subset in subsets] if args.use_existing_split else ["train", "valid", "test"]
- for split in split_names:
- os.makedirs(os.path.join(args.output_dir, IMAGES_DIR, split), exist_ok=True)
- os.makedirs(os.path.join(args.output_dir, LABELS_DIR, split), exist_ok=True)
- split_dict[split] = {}
-
- # Iterate over the subsets to find the page images and labels.
- for subset in subsets:
-
- # Iterate over the pages to create splits at page level.
- for page in tqdm(
- client.paginate(
- "ListElementChildren", id=subset["id"], type="page", recursive=True
- )
- ):
-
- if not args.use_existing_split:
- split = assign_random_split(args.train_prob, args.val_prob)
- else:
- split = subset["name"]
-
- # Extract only pages
- if args.elements_types == ["page"]:
-
- text = extract_transcription(element, no_entities=args.no_entities)
- image = iio.imread(element["zone"]["url"])
-
- if not text:
- logging.warning(f"Skipping {element['id']} (zero or multiple transcriptions with worker_version=None)")
- continue
- else:
- logging.info(f"Processed {element_type} {element['id']}")
- split_dict[split].append(page["id"])
-
- im_path = os.path.join(args.output_dir, IMAGES_DIR, split, f"{element_type}_{element['id']}.jpg")
- txt_path = os.path.join(args.output_dir, LABELS_DIR, split, f"{element_type}_{element['id']}.txt")
-
- save_text(txt_path, text)
- save_image(im_path, image)
-
- # Extract page's children elements (text_zone, text_line)
- else:
- split_dict[split][page["id"]] = {}
-
- for element_type in args.elements_types:
- split_dict[split][page["id"]][element_type] = []
-
- for element in client.paginate("ListElementChildren", id=page["id"], type=element_type, recursive=True):
-
- text = extract_transcription(element, no_entities=args.no_entities)
- image = iio.imread(element["zone"]["url"])
-
- if not text:
- logging.warning(f"Skipping {element_type} {element['id']} (zero or multiple transcriptions with worker_version=None)")
- continue
- else:
- logging.info(f"Processed {element_type} {element['id']}")
- split_dict[split][page["id"]][element_type].append(element['id'])
-
- im_path = os.path.join(args.output_dir, IMAGES_DIR, split, f"{element_type}_{element['id']}.jpg")
- txt_path = os.path.join(args.output_dir, LABELS_DIR, split, f"{element_type}_{element['id']}.txt")
-
- save_text(txt_path, text)
- save_image(im_path, image)
-
- save_json(os.path.join(args.output_dir, "split.json"), split_dict)
diff --git a/Datasets/dataset_formatters/extraction_utils/utils.py b/Datasets/dataset_formatters/extraction_utils/utils.py
deleted file mode 100644
index dc8c67e19b210f16d8175253f65f636a920d1a35..0000000000000000000000000000000000000000
--- a/Datasets/dataset_formatters/extraction_utils/utils.py
+++ /dev/null
@@ -1,78 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
- The utils module
- ======================
-"""
-
-import argparse
-
-def get_cli_args():
- """
- Get the command-line arguments.
- :return: The command-line arguments.
- """
- parser = argparse.ArgumentParser(
- description="Arkindex DAN Training Label Generation"
- )
-
- # Required arguments.
- parser.add_argument(
- "--corpus",
- type=str,
- help="Name of the corpus from which the data will be retrieved.",
- required=True,
- )
- parser.add_argument(
- "--element-type",
- nargs="+",
- type=str,
- help="Type of elements to retrieve",
- required=True,
- )
- parser.add_argument(
- "--parents-types",
- nargs="+",
- type=str,
- help="Type of parents of the elements.",
- required=True,
- )
- parser.add_argument(
- "--output-dir",
- type=str,
- help="Path to the output directory.",
- required=True,
- )
-
- # Optional arguments.
- parser.add_argument(
- "--parents-names",
- nargs="+",
- type=str,
- help="Names of parents of the elements.",
- default=None,
- )
- parser.add_argument(
- "--no-entities",
- action="store_true",
- help="Extract text without entities")
-
- parser.add_argument(
- "--use-existing-split",
- action="store_true",
- help="Do not partition pages into train/val/test")
-
- parser.add_argument(
- "--train-prob",
- type=float,
- default=0.7,
- help="Training set probability")
-
- parser.add_argument(
- "--val-prob",
- type=float,
- default=0.15,
- help="Validation set probability")
-
- return parser.parse_args()
diff --git a/Datasets/dataset_formatters/utils_dataset.py b/Datasets/dataset_formatters/utils_dataset.py
deleted file mode 100644
index f4d980dadb926ceee5f4d13e28620e21a11a1177..0000000000000000000000000000000000000000
--- a/Datasets/dataset_formatters/utils_dataset.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import re
-import random
-import cv2
-import json
-random.seed(42)
-
-
-def natural_sort(l):
- convert = lambda text: int(text) if text.isdigit() else text.lower()
- alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key)]
- return sorted(l, key=alphanum_key)
-
-
-def assign_random_split(train_prob, val_prob):
- """
- assuming train_prob + val_prob + test_prob = 1
- """
- prob = random.random()
- if prob <= train_prob:
- return "train"
- elif prob <= train_prob + val_prob:
- return "val"
- else:
- return "test"
-
-def save_text(path, text):
- with open(path, 'w') as f:
- f.write(text)
-
-def save_image(path, image):
- cv2.imwrite(path, cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
-
-def save_json(path, dict):
- with open(path, "w") as outfile:
- json.dump(dict, outfile, indent=4)
\ No newline at end of file