Update transforms in datamodule/set

1 files changed, 10 insertions, 8 deletions

diff --git a/text_recognizer/data/iam_synthetic_paragraphs.py b/text_recognizer/data/iam_synthetic_paragraphs.py
index f253427..5718747 100644
--- a/text_recognizer/data/iam_synthetic_paragraphs.py
+++ b/text_recognizer/data/iam_synthetic_paragraphs.py
@@ -12,7 +12,6 @@ from text_recognizer.data.base_dataset import (
     BaseDataset,
     convert_strings_to_labels,
 )
-from text_recognizer.data.emnist_mapping import EmnistMapping
 from text_recognizer.data.iam import IAM
 from text_recognizer.data.iam_lines import (
     line_crops_and_labels,
@@ -21,13 +20,13 @@ from text_recognizer.data.iam_lines import (
 )
 from text_recognizer.data.iam_paragraphs import (
     get_dataset_properties,
-    get_target_transform,
-    get_transform,
     IAMParagraphs,
     IMAGE_SCALE_FACTOR,
     NEW_LINE_TOKEN,
     resize_image,
 )
+from text_recognizer.data.mappings.emnist_mapping import EmnistMapping
+from text_recognizer.data.transforms.load_transform import load_transform_from_file
 
 
 PROCESSED_DATA_DIRNAME = (
@@ -83,10 +82,8 @@ class IAMSyntheticParagraphs(IAMParagraphs):
             self.data_train = BaseDataset(
                 data,
                 targets,
-                transform=get_transform(
-                    image_shape=self.dims[1:], augment=self.augment, resize=self.resize
-                ),
-                target_transform=get_target_transform(self.word_pieces),
+                transform=self.transform,
+                target_transform=self.target_transforms,
             )
 
     def __repr__(self) -> str:
@@ -101,6 +98,7 @@ class IAMSyntheticParagraphs(IAMParagraphs):
             return basic
 
         x, y = next(iter(self.train_dataloader()))
+        x = x[0] if isinstance(x, list) else x
         data = (
             f"Train/val/test sizes: {len(self.data_train)}, 0, 0\n"
             f"Train Batch x stats: {(x.shape, x.dtype, x.min(), x.mean(), x.std(), x.max())}\n"
@@ -220,4 +218,8 @@ def generate_random_batches(
 
 def create_synthetic_iam_paragraphs() -> None:
     """Creates and prints IAM Synthetic Paragraphs dataset."""
-    load_and_print_info(IAMSyntheticParagraphs)
+    transform = load_transform_from_file("transform/paragraphs.yaml")
+    test_transform = load_transform_from_file("test_transform/paragraphs.yaml")
+    load_and_print_info(
+        IAMSyntheticParagraphs(transform=transform, test_transform=test_transform)
+    )