Create notas-fiscais.py

notas-fiscais.py

@@ -0,0 +1,58 @@
+import json
+import datasets
+
+_DESCRIPTION = """\
+Dataset com imagens de comprovantes de pagamento e notas ficais no Brasil.
+"""
+_URL_JSON="https://huggingface.co/datasets/gugaime/dokki-pagamentos/raw/main/train.jsonl"
+_URL = "https://huggingface.co/datasets/gugaime/dokki-pagamentos/resolve/main/images.zip"
+
+
+class Dokki(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "id": datasets.Value("string"),
+                    "ner_tags": datasets.Sequence(datasets.ClassLabel(num_classes=5, names=['O', 'cnpj', 'cpf', 'data', 'total'])),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "bboxes": datasets.Sequence(datasets.Sequence(datasets.Value("int64")))
+                }
+            ),
+            # No default supervised_keys (as we have to pass both question
+            # and context as input).
+            supervised_keys=None,
+            homepage="",
+        )
+
+    def _split_generators(self, dl_manager):
+        path = dl_manager.download(_URL)
+        image_iters = dl_manager.iter_archive(path)
+
+        json_path = dl_manager.download(_URL_JSON)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"images": image_iters, "json_path": json_path})
+        ]
+
+    def _generate_examples(self, images, json_path):
+        idx = 0
+        imageMap = {}
+        for filepath, image in images:
+            imageMap[filepath] = {"image": {"path": filepath, "bytes": image.read()}}
+        
+        with open(json_path, 'r') as f:
+            for line in f:
+                data = json.loads(line)
+                path = data["imagePath"]
+                row=imageMap[path]
+                row["id"]=data["id"]
+                row["ner_tags"]=data["labels"]
+                row["tokens"]=data["texts"]
+                bboxex = [ [bbox[0][0], bbox[0][1], bbox[1][0], bbox[1][1]] for bbox in data["bboxes"]]
+                row["bboxes"]=bboxex
+                yield idx, row
+                idx += 1