Define dedicated logger for each module

dan/__init__.py

@@ -5,4 +5,3 @@ logging.basicConfig(
     level=logging.INFO,
     format="%(asctime)s %(levelname)s/%(name)s: %(message)s",
 )
-logger = logging.getLogger(__name__)

dan/datasets/analyze/statistics.py

 # -*- coding: utf-8 -*-
+import logging
 from collections import Counter, defaultdict
 from pathlib import Path
 from typing import Dict, List, Optional
@@ -8,7 +9,7 @@ import numpy as np
 from mdutils.mdutils import MdUtils
 from prettytable import MARKDOWN, PrettyTable
 
-from dan import logger
+logger = logging.getLogger(__name__)
 
 METRIC_COLUMN = "Metric"
 

dan/datasets/extract/extract.py

 # -*- coding: utf-8 -*-
 
 import json
+import logging
 import pickle
 import random
 from collections import defaultdict
@@ -12,7 +13,6 @@ import numpy as np
 from tqdm import tqdm
 
 from arkindex_export import open_database
-from dan import logger
 from dan.datasets.extract.db import (
     Element,
     get_elements,
@@ -37,6 +37,7 @@ IMAGES_DIR = "images"  # Subpath to the images directory.
 
 SPLIT_NAMES = ["train", "val", "test"]
 IIIF_URL_SUFFIX = "/full/full/0/default.jpg"
+logger = logging.getLogger(__name__)
 
 
 class ArkindexExtractor:

dan/ocr/predict/attention.py

 # -*- coding: utf-8 -*-
+import logging
 import re
 from typing import List, Tuple
 
@@ -8,7 +9,7 @@ import torch
 from PIL import Image
 from torchvision.transforms.functional import to_pil_image
 
-from dan import logger
+logger = logging.getLogger(__name__)
 
 
 def parse_delimiters(delimiters: List[str]) -> re.Pattern:

dan/ocr/predict/prediction.py

 # -*- coding: utf-8 -*-
 
 import json
+import logging
 import pickle
 import re
 from itertools import pairwise
@@ -11,7 +12,6 @@ import numpy as np
 import torch
 import yaml
 
-from dan import logger
 from dan.ocr.decoder import GlobalHTADecoder
 from dan.ocr.encoder import FCN_Encoder
 from dan.ocr.predict.attention import (
@@ -29,6 +29,8 @@ from dan.utils import (
     read_image,
 )
 
+logger = logging.getLogger(__name__)
+
 
 class DAN:
     """