Rename mapping to tokenizer

1 files changed, 0 insertions, 78 deletions

diff --git a/text_recognizer/data/mappings/emnist.py b/text_recognizer/data/mappings/emnist.py
deleted file mode 100644
index 331976e..0000000
--- a/text_recognizer/data/mappings/emnist.py
+++ /dev/null
@@ -1,78 +0,0 @@
-"""Emnist mapping."""
-import json
-from pathlib import Path
-from typing import Dict, List, Optional, Sequence, Tuple, Union
-
-import torch
-from torch import Tensor
-
-ESSENTIALS_FILENAME = Path(__file__).parents[0].resolve() / "emnist_essentials.json"
-
-
-class EmnistMapping:
-    """Mapping for EMNIST labels."""
-
-    def __init__(
-        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 = self._load_mapping()
-        if lower:
-            self._to_lower()
-
-    def __len__(self) -> int:
-        return len(self.mapping)
-
-    @property
-    def num_classes(self) -> int:
-        return self.__len__()
-
-    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."""
-
-        def _filter(x: int) -> int:
-            if 40 <= x:
-                return x - 26
-            return x
-
-        self.inverse_mapping = {v: _filter(k) for k, v in enumerate(self.mapping)}
-        self.mapping = [c for c in self.mapping if not c.isupper()]
-
-    def get_token(self, index: Union[int, Tensor]) -> str:
-        """Returns token for index value."""
-        if (index := int(index)) <= len(self.mapping):
-            return self.mapping[index]
-        raise KeyError(f"Index ({index}) not in mapping.")
-
-    def get_index(self, token: str) -> Tensor:
-        """Returns index value of token."""
-        if token in self.inverse_mapping:
-            return torch.LongTensor([self.inverse_mapping[token]])
-        raise KeyError(f"Token ({token}) not found in inverse mapping.")
-
-    def get_text(self, indices: Union[List[int], Tensor]) -> str:
-        """Returns the text from a list of indices."""
-        if isinstance(indices, Tensor):
-            indices = indices.tolist()
-        return "".join([self.mapping[index] for index in indices])
-
-    def get_indices(self, text: str) -> Tensor:
-        """Returns tensor of indices for a string."""
-        return Tensor([self.inverse_mapping[token] for token in text])
-
-    def __getitem__(self, x: Union[int, Tensor]) -> str:
-        """Returns text for a list of indices."""
-        return self.get_token(x)