Upload docbank.py

docbank.py

@@ -57,7 +57,7 @@ _FEATURES = datasets.Features(
     {
         "id": datasets.Value("string"),
         "input_ids": datasets.Sequence(datasets.Value("int64")),
-        "bboxes": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
+        "bbox": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
         "RGBs": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))),
         "fonts": datasets.Sequence(datasets.Value("string")),
         "image": datasets.Array3D(shape=(3, 224, 224), dtype="uint8"),
@@ -70,12 +70,6 @@ _FEATURES = datasets.Features(
     }
 )
 
-_DEFUNCT_FILE_IDS = [
-    '126.tar_1706.03360.gz_dispersion_v2_7', '119.tar_1606.07466.gz_20160819Draft_8',
-    '167.tar_1412.4821.gz_IDM_TD_Paper_16', '17.tar_1701.07437.gz_muon-beam-dump_final_2',
-    '31.tar_1702.04307.gz_held-karp_21', '7.tar_1401.4493.gz_ReversibleNoise_2'
-]
-
 
 def load_image(image_path, size=None):
     image = Image.open(image_path).convert("RGB")
@@ -231,18 +225,20 @@ class Docbank(datasets.GeneratorBasedBuilder):
                 with open(f_fp_txt, newline='', encoding='utf-8') as csvfile:
                     reader = csv.reader(csvfile, delimiter='\t', quotechar=' ')
                     for row in reader:
-                        #if f_id == '121.tar_1606.08710.gz_mutualEnergy_05_77':
+                        normalized_bbox = normalize_bbox(row[1:5], size)
                         tokenized_input = self.TOKENIZER(
                             row[0],
                             add_special_tokens=False,
                             return_offsets_mapping=False,
                             return_attention_mask=False,
                         )
-                        tokens.append(tokenized_input['input_ids'][0] if len(tokenized_input['input_ids']) == 1 else self.TOKENIZER.unk_token_id)
-                        bboxes.append(normalize_bbox(row[1:5], size))
-                        rgbs.append(row[5:8])
-                        fonts.append(row[8])
-                        labels.append(row[9])
+                        for tkn in tokenized_input['input_ids']:
+                            tokens.append(tkn)
+                            bboxes.append(normalized_bbox)
+                            rgbs.append(row[5:8])
+                            fonts.append(row[8])
+                            labels.append(row[9])
+
             except:
                 continue
 
@@ -264,7 +260,7 @@ class Docbank(datasets.GeneratorBasedBuilder):
                 yield key, {
                     "id": f"{f_id}_{chunk_id}",
                     'input_ids': split_tokens,
-                    "bboxes": split_bboxes,
+                    "bbox": split_bboxes,
                     "RGBs": split_rgbs,
                     "fonts": split_fonts,
                     "image": image,