Add SaintGallDataset class

hwd/datasets/saint_gall.py

@@ -1,23 +1,58 @@
 from .base_dataset import BaseDataset
 from pathlib import Path
+from .shtg.base_dataset import extract_zip, download_file
 
 
+SAINTGALL_URL = 'https://github.com/aimagelab/HWD/releases/download/saintgall/saintgalldb-v1.0.zip'
+SAINTGALL_ZIP_PATH = Path('~/.cache/saintgall/saintgalldb-v1.0.zip').expanduser()
+SAINTGALL_DIR_PATH = Path('~/.cache/saintgall').expanduser()
+
+SPECIAL_MAP = {
+    "pt": ".",
+    "et": "&",
+}
+
 class SaintGallDataset(BaseDataset):
-    def __init__(self, path, transform=None, nameset=None):
-        """
-        Args:
-            path (string): Path folder of the dataset.
-            transform (callable, optional): Optional transform to be applied
-                on a sample.
-            author_ids (list, optional): List of authors to consider.
-            nameset (string, optional): Name of the dataset.
-            max_samples (int, optional): Maximum number of samples to consider.
-        """
-        super().__init__(path, transform, nameset)
+    def __init__(self, transform=None, nameset='train', dataset_type='lines'):
+        if not SAINTGALL_DIR_PATH.exists():
+            download_file(SAINTGALL_URL, SAINTGALL_ZIP_PATH)
+            extract_zip(SAINTGALL_ZIP_PATH, SAINTGALL_DIR_PATH, delete=True)
+        saintgall_unzip_path = SAINTGALL_DIR_PATH / 'saintgalldb-v1.0'
 
-        self.path = Path(self.path) / 'data' / 'line_images_normalized'
-        self.imgs = list(self.path.rglob('*.png'))
+        nameset_path = saintgall_unzip_path / 'sets' / f'{nameset}.txt'
+        assert nameset_path.exists(), f'The nameset file {nameset_path} does not exist at the specified path {nameset_path}'
+        split_ids = set(nameset_path.read_text().splitlines())
 
-        self.author_ids = [0, ]
-        self.labels = [0, ] * len(self.imgs)
+        if dataset_type == 'lines':
+            self.path = saintgall_unzip_path / 'data' / 'line_images'
+        elif dataset_type == 'lines_normalized':
+            self.path = saintgall_unzip_path / 'data' / 'line_images_normalized'
+        else:
+            raise ValueError(f'Invalid dataset_type: {dataset_type}. Available types: ["lines", "lines_normalized"]')
+
+        self.imgs = list(self.path.rglob('*.png'))
+        self.imgs = [img for img in self.imgs if img.stem[:10] in split_ids]
+
+        self.author_ids = [0, ] * len(self.imgs)  # All samples are from the same author
+        super().__init__(
+            saintgall_unzip_path,
+            self.imgs,
+            self.author_ids,
+            [0, ],  # All samples are from the same author
+            transform=transform,
+        )
 
+        labels_path = saintgall_unzip_path / 'ground_truth' / 'transcription.txt'
+        self.labels_dict = {}
+        for line in labels_path.read_text().splitlines():
+            img_id, label, _ = line.split(' ')
+            label = label.replace('|', '- -').split('-')
+            for i in range(len(label)):
+                if len(label[i]) > 1:
+                    label[i] = SPECIAL_MAP[label[i]]
+            label = ''.join(label)
+            self.labels_dict[img_id] = label
+
+        self.labels = [self.labels_dict[img.stem] for img in self.imgs]
+        self.has_labels = True
+