data added

.gitattributes

@@ -52,3 +52,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+*.txt filter=lfs diff=lfs merge=lfs -text

gt.txt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23cd8c09f536e7071daa599e27050e9ca2d77aa10f779800441682079af5337d
+size 17156170

img.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b9eac786287a42e2cb65aa7fe512e33bebe54228525a8efcae3f9fa93f982b3b
+size 7151880919

synthetic_cyrillic.py

@@ -0,0 +1,50 @@
+import os
+import pandas as pd
+import zipfile
+
+import datasets
+from datasets import load_dataset
+
+
+class SyntheticCyrillic(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "path": datasets.Value("string"),
+                    "name": datasets.Value("string"),
+                    "text": datasets.Value("string")   
+                }
+            )
+        )
+
+    def _split_generators(self, dl_manager):
+        _URLS = {"img": "img.zip", "labels": "gt.txt"}
+        data_paths = dl_manager.download_and_extract(_URLS)
+
+        return [datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "image_paths": dl_manager.iter_files(data_paths["img"]),
+                        "labels_path": data_paths["labels"]
+                    })]
+
+    def _generate_examples(self, image_paths, labels_path):
+        df = pd.read_csv(labels_path, sep=",", names=["path", "text"])
+        df["path"] = df.path.str[4:]
+        df.set_index("path", inplace=True)
+
+        for image_path in image_paths:
+            image_name = os.path.basename(image_path)
+ 
+            if image_name in df.index:
+
+                example = {
+                    "image": image_path,
+                    "path": image_path,
+                    "name": image_name,
+                    "text": df["text"][image_name]
+                }
+                yield image_name, example