WIP mappings

7 files changed, 43 insertions, 35 deletions

diff --git a/text_recognizer/data/base_data_module.py b/text_recognizer/data/base_data_module.py
index 6306cf8..77d15e5 100644
--- a/text_recognizer/data/base_data_module.py
+++ b/text_recognizer/data/base_data_module.py
@@ -6,7 +6,7 @@ from pytorch_lightning import LightningDataModule
 from torch.utils.data import DataLoader
 
 from text_recognizer.data.base_dataset import BaseDataset
-from text_recognizer.data.mappings.base import AbstractMapping
+from text_recognizer.data.mappings import AbstractMapping
 
 T = TypeVar("T")
 
diff --git a/text_recognizer/data/base_dataset.py b/text_recognizer/data/base_dataset.py
index 675683a..4ceb818 100644
--- a/text_recognizer/data/base_dataset.py
+++ b/text_recognizer/data/base_dataset.py
@@ -32,13 +32,6 @@ class BaseDataset(Dataset):
         self.targets = targets
         self.transform = transform
         self.target_transform = target_transform
-
-    def __attrs_pre_init__(self) -> None:
-        """Pre init constructor."""
-        super().__init__()
-
-    def __attrs_post_init__(self) -> None:
-        """Post init constructor."""
         if len(self.data) != len(self.targets):
             raise ValueError("Data and targets must be of equal length.")
         self.transform = self._load_transform(self.transform)
diff --git a/text_recognizer/data/emnist.py b/text_recognizer/data/emnist.py
index 1b1381a..ea27984 100644
--- a/text_recognizer/data/emnist.py
+++ b/text_recognizer/data/emnist.py
@@ -102,22 +102,6 @@ class EMNIST(BaseDataModule):
         return basic + data
 
 
-def emnist_mapping(
-    extra_symbols: Optional[Set[str]] = None,
-) -> Tuple[List, Dict[str, int], List[int]]:
-    """Return the EMNIST mapping."""
-    if not ESSENTIALS_FILENAME.exists():
-        download_and_process_emnist()
-    with ESSENTIALS_FILENAME.open() as f:
-        essentials = json.load(f)
-    mapping = list(essentials["characters"])
-    if extra_symbols is not None:
-        mapping += extra_symbols
-    inverse_mapping = {v: k for k, v in enumerate(mapping)}
-    input_shape = essentials["input_shape"]
-    return mapping, inverse_mapping, input_shape
-
-
 def download_and_process_emnist() -> None:
     """Downloads and preprocesses EMNIST dataset."""
     metadata = toml.load(METADATA_FILENAME)
diff --git a/text_recognizer/data/iam_lines.py b/text_recognizer/data/iam_lines.py
index 5f38f14..c23dec6 100644
--- a/text_recognizer/data/iam_lines.py
+++ b/text_recognizer/data/iam_lines.py
@@ -5,7 +5,7 @@ dataset.
 """
 import json
 from pathlib import Path
-from typing import List, Sequence, Tuple
+from typing import Callable, List, Optional, Sequence, Tuple, Type
 
 from loguru import logger as log
 import numpy as np
@@ -19,7 +19,7 @@ from text_recognizer.data.base_dataset import (
     split_dataset,
 )
 from text_recognizer.data.iam import IAM
-from text_recognizer.data.mappings.emnist import EmnistMapping
+from text_recognizer.data.mappings import AbstractMapping, EmnistMapping
 from text_recognizer.data.transforms.load_transform import load_transform_from_file
 from text_recognizer.data.utils import image_utils
 
@@ -37,8 +37,27 @@ MAX_WORD_PIECE_LENGTH = 72
 class IAMLines(BaseDataModule):
     """IAM handwritten lines dataset."""
 
-    def __init__(self) -> None:
-        super().__init__()
+    def __init__(
+        self,
+        mapping: Type[AbstractMapping],
+        transform: Optional[Callable] = None,
+        test_transform: Optional[Callable] = None,
+        target_transform: Optional[Callable] = None,
+        train_fraction: float = 0.8,
+        batch_size: int = 16,
+        num_workers: int = 0,
+        pin_memory: bool = True,
+    ) -> None:
+        super().__init__(
+            mapping,
+            transform,
+            test_transform,
+            target_transform,
+            train_fraction,
+            batch_size,
+            num_workers,
+            pin_memory,
+        )
         self.dims = (1, IMAGE_HEIGHT, IMAGE_WIDTH)
         self.output_dims = (MAX_LABEL_LENGTH, 1)
 
diff --git a/text_recognizer/data/iam_paragraphs.py b/text_recognizer/data/iam_paragraphs.py
index dde505d..9c75129 100644
--- a/text_recognizer/data/iam_paragraphs.py
+++ b/text_recognizer/data/iam_paragraphs.py
@@ -16,7 +16,7 @@ from text_recognizer.data.base_dataset import (
     split_dataset,
 )
 from text_recognizer.data.iam import IAM
-from text_recognizer.data.mappings.emnist import EmnistMapping
+from text_recognizer.data.mappings import EmnistMapping
 from text_recognizer.data.transforms.load_transform import load_transform_from_file
 
 
diff --git a/text_recognizer/data/iam_synthetic_paragraphs.py b/text_recognizer/data/iam_synthetic_paragraphs.py
index 2e7762c..1dc517d 100644
--- a/text_recognizer/data/iam_synthetic_paragraphs.py
+++ b/text_recognizer/data/iam_synthetic_paragraphs.py
@@ -24,7 +24,7 @@ from text_recognizer.data.iam_paragraphs import (
     NEW_LINE_TOKEN,
     resize_image,
 )
-from text_recognizer.data.mappings.emnist import EmnistMapping
+from text_recognizer.data.mappings import EmnistMapping
 from text_recognizer.data.transforms.load_transform import load_transform_from_file
 
 
diff --git a/text_recognizer/data/mappings/emnist.py b/text_recognizer/data/mappings/emnist.py
index 51e4677..ecd862e 100644
--- a/text_recognizer/data/mappings/emnist.py
+++ b/text_recognizer/data/mappings/emnist.py
@@ -1,12 +1,15 @@
 """Emnist mapping."""
-from typing import List, Optional, Sequence, Union
+import json
+from pathlib import Path
+from typing import Dict, List, Optional, Sequence, Union, Tuple
 
 import torch
 from torch import Tensor
 
-from text_recognizer.data.emnist import emnist_mapping
 from text_recognizer.data.mappings.base import AbstractMapping
 
+ESSENTIALS_FILENAME = Path(__file__).parents[0].resolve() / "emnist_essentials.json"
+
 
 class EmnistMapping(AbstractMapping):
     """Mapping for EMNIST labels."""
@@ -15,13 +18,22 @@ class EmnistMapping(AbstractMapping):
         self, extra_symbols: Optional[Sequence[str]] = None, lower: bool = True
     ) -> None:
         self.extra_symbols = set(extra_symbols) if extra_symbols is not None else None
-        self.mapping, self.inverse_mapping, self.input_size = emnist_mapping(
-            self.extra_symbols
-        )
+        self.mapping, self.inverse_mapping, self.input_size = self._load_mapping()
         if lower:
             self._to_lower()
         super().__init__(self.input_size, self.mapping, self.inverse_mapping)
 
+    def _load_mapping(self) -> Tuple[List, Dict[str, int], List[int]]:
+        """Return the EMNIST mapping."""
+        with ESSENTIALS_FILENAME.open() as f:
+            essentials = json.load(f)
+        mapping = list(essentials["characters"])
+        if self.extra_symbols is not None:
+            mapping += self.extra_symbols
+        inverse_mapping = {v: k for k, v in enumerate(mapping)}
+        input_shape = essentials["input_shape"]
+        return mapping, inverse_mapping, input_shape
+
     def _to_lower(self) -> None:
         """Converts mapping to lowercase letters only."""