More linting

See #557.

kraken/blla.py

@@ -390,7 +390,6 @@ def segment(im: PIL.Image.Image,
 
     # create objects and assign IDs
     blls = []
-    reg_idx = 0
     _shp_regs = {}
     for reg_type, rgs in regions.items():
         for reg in rgs:

kraken/containers.py

@@ -1,5 +1,24 @@
-
-import PIL.Image
+#
+# Copyright 2023 Benjamin Kiessling
+#
+# 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.
+"""
+kraken.containers
+~~~~~~~~~~~~~~~~~
+
+Container classes replacing the old dictionaries returned by kraken's
+functional blocks.
+"""
 import numpy as np
 import bidi.algorithm as bd
 
@@ -187,9 +206,9 @@ class ocr_record(ABC):
     def __init__(self,
                  prediction: str,
                  cuts: List[Union[Tuple[int, int], Tuple[Tuple[int, int],
-                                                             Tuple[int, int],
-                                                             Tuple[int, int],
-                                                             Tuple[int, int]]]],
+                                                         Tuple[int, int],
+                                                         Tuple[int, int],
+                                                         Tuple[int, int]]]],
                  confidences: List[float],
                  display_order: bool = True) -> None:
         self._prediction = prediction
@@ -463,9 +482,9 @@ class BBoxOCRRecord(ocr_record, BBoxLine):
     def __init__(self,
                  prediction: str,
                  cuts: List[Tuple[Tuple[int, int],
-                                      Tuple[int, int],
-                                      Tuple[int, int],
-                                      Tuple[int, int]]],
+                                  Tuple[int, int],
+                                  Tuple[int, int],
+                                  Tuple[int, int]]],
                  confidences: List[float],
                  line: Union[BBoxLine, Dict[str, Any]],
                  base_dir: Optional[Literal['L', 'R']] = None,
@@ -593,5 +612,3 @@ def _reorder(self, base_dir: Optional[Literal['L', 'R']] = None) -> 'BBoxOCRReco
                             base_dir=base_dir,
                             display_order=not self._display_order)
         return rec
-
-

kraken/lib/arrow_dataset.py

@@ -34,7 +34,7 @@
 from kraken.lib.xml import XMLPage
 from kraken.lib.util import is_bitonal, make_printable
 from kraken.lib.exceptions import KrakenInputException
-from os import extsep, PathLike
+from os import PathLike
 
 import logging
 

kraken/lib/codec.py

@@ -169,9 +169,9 @@ def decode(self, labels: Sequence[Tuple[int, int, int, float]]) -> List[Tuple[st
             if int(labels[idx]) in self.l2c_single:
                 code = self.l2c_single[int(labels[idx])]
                 decoded.extend([(c, s, e, u) for c, s, e, u in zip(code,
-                                                                    len(code) * [start[idx]],
-                                                                    len(code) * [end[idx]],
-                                                                    len(code) * [con[idx]])])
+                                                                   len(code) * [start[idx]],
+                                                                   len(code) * [end[idx]],
+                                                                   len(code) * [con[idx]])])
                 idx += 1
                 decodable_suffix = True
             else:

kraken/lib/layers.py

@@ -12,7 +12,7 @@
 
 logger = logging.getLogger('coremltools')
 logger.setLevel(logging.ERROR)
-from coremltools.proto import NeuralNetwork_pb2
+from coremltools.proto import NeuralNetwork_pb2  # NOQA
 logger.setLevel(logging.WARNING)
 
 # all tensors are ordered NCHW, the "feature" dimension is C, so the output of
@@ -745,6 +745,7 @@ def resize(self, output_size: int, del_indices: Optional[Iterable[int]] = None)
         self.lin.weight = torch.nn.Parameter(weight)
         self.lin.bias = torch.nn.Parameter(bias)
 
+
 class ActConv2D(Module):
     """
     A wrapper for convolution + activation with automatic padding ensuring no
@@ -760,7 +761,7 @@ def __init__(self, in_channels: int, out_channels: int, kernel_size: Tuple[int,
         self.dilation = dilation
         self.padding = tuple((dilation[i] * (kernel_size[i] - 1)) // 2 for i in range(2))
         self.transposed = transposed
-        
+
         if nl == 's':
             self.nl = torch.sigmoid
             self.nl_name = 'SIGMOID'
@@ -779,7 +780,7 @@ def __init__(self, in_channels: int, out_channels: int, kernel_size: Tuple[int,
         else:
             self.nl_name = 'LINEAR'
             self.nl = lambda x: x
-        
+
         if self.transposed:
             self.co = torch.nn.ConvTranspose2d(in_channels, out_channels, kernel_size,
                                   stride=stride, padding=self.padding, dilation=self.dilation)
@@ -799,8 +800,8 @@ def forward(self, inputs: torch.Tensor, seq_len: Optional[torch.Tensor] = None,
         if seq_len is not None:
             if self.transposed:
                 seq_len = torch.floor(
-                    ((seq_len - 1) * self.stride[1]\
-                        - 2 * self.padding[1]\
+                    ((seq_len - 1) * self.stride[1]
+                        - 2 * self.padding[1]
                         + self.dilation[1] * (self.kernel_size[1] - 1)
                         + 1))
             else:

kraken/lib/pretrain/model.py

@@ -43,6 +43,8 @@
 from pytorch_lightning.callbacks import EarlyStopping
 from pytorch_lightning.utilities.memory import is_oom_error, garbage_collection_cuda
 
+from kraken.containers import Segmentation
+
 from kraken.lib import vgsl, default_specs, layers
 from kraken.lib.xml import XMLPage
 from kraken.lib.util import parse_gt_path
@@ -371,14 +373,6 @@ def validation_step(self, batch, batch_idx):
         o = self._step(batch, batch_idx)
         if o is not None:
             logits, targets, loss = o
-            with torch.no_grad():
-                if logits.numel() == 0:
-                    corr = 0
-                else:
-                    _max = logits.argmax(-1) == 0
-                    _min = logits.argmin(-1) == 0
-                    both = _max & _min
-                    corr = _max.long().sum().item() - both.long().sum().item()
             self.val_ce.append(loss.cpu())
             self.log('CE', loss, on_step=True, on_epoch=True)
 

kraken/lib/progress.py

@@ -15,22 +15,21 @@
 """
 Handlers for rich-based progress bars.
 """
-from typing import Any, Dict, Optional, Union
-from numbers import Number
+from typing import Union
 from dataclasses import dataclass
 
-import pytorch_lightning as pl
 from pytorch_lightning.callbacks.progress.rich_progress import CustomProgress, RichProgressBar, MetricsTextColumn
 
 from rich import get_console, reconfigure
-from rich.console import Console, RenderableType
-from rich.progress import BarColumn, Progress, ProgressColumn, Task, TextColumn, TimeRemainingColumn, TimeElapsedColumn, DownloadColumn
+from rich.console import RenderableType
+from rich.progress import BarColumn, Progress, ProgressColumn, TextColumn, TimeRemainingColumn, TimeElapsedColumn, DownloadColumn
 from rich.text import Text
 from rich.style import Style
 from rich.default_styles import DEFAULT_STYLES
 
 __all__ = ['KrakenProgressBar', 'KrakenDownloadProgressBar', 'KrakenTrainProgressBar']
 
+
 class BatchesProcessedColumn(ProgressColumn):
     def __init__(self):
         super().__init__()
@@ -130,6 +129,7 @@ def _get_train_description(self, current_epoch: int) -> str:
         return f"stage {current_epoch}/" \
                f"{self.trainer.max_epochs if self.trainer.model.hparams.hyper_params['quit'] == 'fixed' else '∞'}"
 
+
 @dataclass
 class RichProgressBarTheme:
     """Styles to associate to different base components.

kraken/lib/util.py

@@ -10,12 +10,13 @@
 from PIL import Image
 from os import PathLike
 
-from typing import Union, Callable
+from typing import Union, Callable, Optional, Literal
 
-from kraken.containers import BBoxLine
 from kraken.lib import functional_im_transforms as F_t
+from kraken.containers import BBoxLine
+from kraken.exceptions import KrakenInputException
 
-__all__ = ['pil2array', 'array2pil', 'is_bitonal', 'make_printable', 'get_im_str', 'parse_path']
+__all__ = ['pil2array', 'array2pil', 'is_bitonal', 'make_printable', 'get_im_str', 'parse_gt_path']
 
 
 def pil2array(im: Image.Image, alpha: int = 0) -> np.ndarray:
@@ -122,7 +123,7 @@ def parse_gt_path(path: Union[str, PathLike],
     try:
         with Image.open(path) as im:
             w, h = im.size
-    except Exception e:
+    except Exception as e:
         raise KrakenInputException(e)
 
     gt = ''
@@ -137,7 +138,7 @@ def parse_gt_path(path: Union[str, PathLike],
         raise KrakenInputException(f'No text for ground truth line {path}.')
 
     return BBoxLine(id=uuid.uuid4(),
-                    bbox=((0,0), (w,0), (w,h), (0,h)),
+                    bbox=((0, 0), (w, 0), (w, h), (0, h)),
                     text=gt,
                     base_dir=base_dir,
                     imagename=path,

kraken/lib/vgsl.py

@@ -5,7 +5,6 @@
 import json
 import torch
 import logging
-import warnings
 
 from torch import nn
 from os import PathLike
@@ -496,7 +495,7 @@ def build_dropout(self,
                       input: Tuple[int, int, int, int],
                       blocks: List[str],
                       idx: int,
-                  target_output_shape: Optional[Tuple[int, int, int, int]] = None) -> Union[Tuple[None, None, None], Tuple[Tuple[int, int, int, int], str, Callable]]:
+                      target_output_shape: Optional[Tuple[int, int, int, int]] = None) -> Union[Tuple[None, None, None], Tuple[Tuple[int, int, int, int], str, Callable]]:
         pattern = re.compile(r'(?P<type>Do)(?P<name>{\w+})?(?P<p>(\d+(\.\d*)?|\.\d+))?(,(?P<dim>\d+))?')
         m = pattern.match(blocks[idx])
         if not m:
@@ -735,7 +734,7 @@ def _bracket_count(self, block: str) -> int:
             elif c != ")":
                 break
         return rst
-    
+
     def _parenthesis_count(self, block: str) -> int:
         rst = 0
         for c in block:
@@ -777,7 +776,7 @@ def build_series(self,
         named_spec[0]._block = '[' + named_spec[0]._block
         named_spec[-1]._block = named_spec[-1]._block + ']'
         return oshape, named_spec, nn
-    
+
     def build_parallel(self,
                        input: Tuple[int, int, int, int],
                        blocks: List[str],

kraken/lib/xml.py

@@ -23,13 +23,10 @@
 
 from itertools import groupby
 from lxml import etree
-from PIL import Image
 from typing import Union, Dict, Any, Sequence, Tuple, Literal, Optional, List
 
 from collections import defaultdict
 from kraken.containers import Segmentation, BaselineLine, Region
-from kraken.lib.segmentation import calculate_polygonal_environment
-from kraken.lib.exceptions import KrakenInputException
 
 logger = logging.getLogger(__name__)
 
@@ -247,7 +244,7 @@ def _parse_group(el):
                     _ro = []
                     if el.tag.endswith('UnorderedGroup'):
                         _ro = [_parse_group(x) for x in el.iterchildren()]
-                        is_total = False
+                        is_total = False  # NOQA
                     elif el.tag.endswith('OrderedGroup'):
                         _ro.extend(_parse_group(x) for x in el.iterchildren())
                     else:
@@ -306,7 +303,6 @@ def _parse_page(self):
 
             self._tag_set = set(('default',))
             tmp_transkribus_line_order = defaultdict(list)
-            valid_tr_lo = True
 
             for region in regions:
                 if not any([True if region.tag.endswith(k) else False for k in page_regions.keys()]):
@@ -329,7 +325,7 @@ def _parse_page(self):
                     if not rtype and 'structure' in cs and 'type' in cs['structure']:
                         rtype = cs['structure']['type']
                     # transkribus-style reading order
-                    if 'readingOrder' in cs and 'index'in cs['readingOrder']:
+                    if 'readingOrder' in cs and 'index' in cs['readingOrder']:
                         tr_region_order.append((region.get('id'), int(cs['readingOrder']['index'])))
                 # fall back to default region type if nothing is given
                 if not rtype:
@@ -388,7 +384,6 @@ def _parse_page(self):
                             reg_cus = self._parse_page_custom(line.getparent().get('custom'))
                             if 'readingOrder' not in reg_cus or 'index' not in reg_cus['readingOrder']:
                                 logger.warning('Incomplete `custom` attribute reading order found.')
-                                valid_tr_lo = False
                             else:
                                 tmp_transkribus_line_order[int(reg_cus['readingOrder']['index'])].append((int(cs['readingOrder']['index']), line.get('id')))
 
@@ -433,7 +428,7 @@ def _parse_group(el):
                     _ro = []
                     if el.tag.endswith('UnorderedGroup'):
                         _ro = [_parse_group(x) for x in el.iterchildren()]
-                        is_total = False
+                        is_total = False  # NOQA
                     elif el.tag.endswith('OrderedGroup'):
                         _ro.extend(_parse_group(x) for x in el.iterchildren())
                     else:

kraken/transcribe.py

@@ -18,6 +18,7 @@
 from kraken.lib.exceptions import KrakenInputException
 from kraken.lib.util import get_im_str
 
+from typing import List
 from jinja2 import Environment, PackageLoader
 from io import BytesIO