Efficient net and non working transformer model.

5 files changed, 19 insertions, 24 deletions

diff --git a/text_recognizer/data/iam_extended_paragraphs.py b/text_recognizer/data/iam_extended_paragraphs.py
index 2380660..0a30a42 100644
--- a/text_recognizer/data/iam_extended_paragraphs.py
+++ b/text_recognizer/data/iam_extended_paragraphs.py
@@ -19,18 +19,10 @@ class IAMExtendedParagraphs(BaseDataModule):
         super().__init__(batch_size, num_workers)
 
         self.iam_paragraphs = IAMParagraphs(
-            batch_size,
-            num_workers,
-            train_fraction,
-            augment,
-            word_pieces,
+            batch_size, num_workers, train_fraction, augment, word_pieces,
         )
         self.iam_synthetic_paragraphs = IAMSyntheticParagraphs(
-            batch_size,
-            num_workers,
-            train_fraction,
-            augment,
-            word_pieces,
+            batch_size, num_workers, train_fraction, augment, word_pieces,
         )
 
         self.dims = self.iam_paragraphs.dims
diff --git a/text_recognizer/data/iam_paragraphs.py b/text_recognizer/data/iam_paragraphs.py
index 62c44f9..24409bc 100644
--- a/text_recognizer/data/iam_paragraphs.py
+++ b/text_recognizer/data/iam_paragraphs.py
@@ -101,7 +101,7 @@ class IAMParagraphs(BaseDataModule):
                 data,
                 targets,
                 transform=get_transform(image_shape=self.dims[1:], augment=augment),
-                target_transform=get_target_transform(self.word_pieces)
+                target_transform=get_target_transform(self.word_pieces),
             )
 
         logger.info(f"Loading IAM paragraph regions and lines for {stage}...")
@@ -162,10 +162,7 @@ def get_dataset_properties() -> Dict:
             "min": min(_get_property_values("num_lines")),
             "max": max(_get_property_values("num_lines")),
         },
-        "crop_shape": {
-            "min": crop_shapes.min(axis=0),
-            "max": crop_shapes.max(axis=0),
-        },
+        "crop_shape": {"min": crop_shapes.min(axis=0), "max": crop_shapes.max(axis=0),},
         "aspect_ratio": {
             "min": aspect_ratio.min(axis=0),
             "max": aspect_ratio.max(axis=0),
@@ -286,9 +283,7 @@ def get_transform(image_shape: Tuple[int, int], augment: bool) -> transforms.Com
             ),
             transforms.ColorJitter(brightness=(0.8, 1.6)),
             transforms.RandomAffine(
-                degrees=1,
-                shear=(-10, 10),
-                interpolation=InterpolationMode.BILINEAR,
+                degrees=1, shear=(-10, 10), interpolation=InterpolationMode.BILINEAR,
             ),
         ]
     else:
@@ -296,10 +291,12 @@ def get_transform(image_shape: Tuple[int, int], augment: bool) -> transforms.Com
     transforms_list.append(transforms.ToTensor())
     return transforms.Compose(transforms_list)
 
+
 def get_target_transform(word_pieces: bool) -> Optional[transforms.Compose]:
     """Transform emnist characters to word pieces."""
     return transforms.Compose([WordPiece()]) if word_pieces else None
 
+
 def _labels_filename(split: str) -> Path:
     """Return filename of processed labels."""
     return PROCESSED_DATA_DIRNAME / split / "_labels.json"
diff --git a/text_recognizer/data/iam_synthetic_paragraphs.py b/text_recognizer/data/iam_synthetic_paragraphs.py
index 4ccc5c2..78e6c05 100644
--- a/text_recognizer/data/iam_synthetic_paragraphs.py
+++ b/text_recognizer/data/iam_synthetic_paragraphs.py
@@ -97,7 +97,7 @@ class IAMSyntheticParagraphs(IAMParagraphs):
                 transform=get_transform(
                     image_shape=self.dims[1:], augment=self.augment
                 ),
-                target_transform=get_target_transform(self.word_pieces)
+                target_transform=get_target_transform(self.word_pieces),
             )
 
     def __repr__(self) -> str:
diff --git a/text_recognizer/data/mappings.py b/text_recognizer/data/mappings.py
index f4016ba..190febe 100644
--- a/text_recognizer/data/mappings.py
+++ b/text_recognizer/data/mappings.py
@@ -58,13 +58,13 @@ class WordPieceMapping(EmnistMapping):
     def __init__(
         self,
         num_features: int = 1000,
-        tokens: str = "iamdb_1kwp_tokens_1000.txt" ,
+        tokens: str = "iamdb_1kwp_tokens_1000.txt",
         lexicon: str = "iamdb_1kwp_lex_1000.txt",
         data_dir: Optional[Union[str, Path]] = None,
         use_words: bool = False,
         prepend_wordsep: bool = False,
         special_tokens: Sequence[str] = ("<s>", "<e>", "<p>"),
-        extra_symbols: Optional[Sequence[str]] = ("\n", ),
+        extra_symbols: Optional[Sequence[str]] = ("\n",),
     ) -> None:
         super().__init__(extra_symbols)
         self.wordpiece_processor = self._configure_wordpiece_processor(
@@ -90,7 +90,13 @@ class WordPieceMapping(EmnistMapping):
         extra_symbols: Optional[Sequence[str]],
     ) -> Preprocessor:
         data_dir = (
-            (Path(__file__).resolve().parents[2] / "data" / "downloaded" / "iam" / "iamdb")
+            (
+                Path(__file__).resolve().parents[2]
+                / "data"
+                / "downloaded"
+                / "iam"
+                / "iamdb"
+            )
             if data_dir is None
             else Path(data_dir)
         )
diff --git a/text_recognizer/data/transforms.py b/text_recognizer/data/transforms.py
index 8d1bedd..d0f1f35 100644
--- a/text_recognizer/data/transforms.py
+++ b/text_recognizer/data/transforms.py
@@ -13,7 +13,7 @@ class WordPiece:
     def __init__(
         self,
         num_features: int = 1000,
-        tokens: str = "iamdb_1kwp_tokens_1000.txt" ,
+        tokens: str = "iamdb_1kwp_tokens_1000.txt",
         lexicon: str = "iamdb_1kwp_lex_1000.txt",
         data_dir: Optional[Union[str, Path]] = None,
         use_words: bool = False,
@@ -35,4 +35,4 @@ class WordPiece:
         self.max_len = max_len
 
     def __call__(self, x: Tensor) -> Tensor:
-        return self.mapping.emnist_to_wordpiece_indices(x)[:self.max_len]
+        return self.mapping.emnist_to_wordpiece_indices(x)[: self.max_len]