Upload Corrosion.py

Corrosion.py

@@ -0,0 +1,67 @@
+import copy
+import json
+import os
+import pandas as pd
+from glob import glob
+import datasets
+from datasets import load_dataset
+
+_CITATION = """\
+
+"""
+_DESCRIPTION = """\
+
+"""
+
+_SPLITS = ["train", "test"]
+
+#Your zip url
+_URL = "https://huggingface.co/datasets/Dodon/Corrosion/blob/main/original-20231018T064149Z-001.zip"
+
+class CorrisonData(datasets.GeneratorBasedBuilder):
+    
+    def _info(self):
+        features = datasets.Features(
+            {
+                "imgname": datasets.Value("string"),
+                "image": datasets.Image(),
+                "label": datasets.Value("int64")
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download_and_extract(_URL) + "/original"
+        
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "label_path": downloaded_file + "/Train/json",
+                    "images_path": downloaded_file + "/Train/images",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "label_path": downloaded_file + "/Test/json",
+                    "images_path": downloaded_file + "/Test/images",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, label_path:str, images_path: str):
+        idx = 0
+        for json_path in glob(os.path.join(label_path, '/*.json')):
+            fname = os.path.basename(json_path).split('.')[0]
+
+            with open(json_path) as f:
+                data = json.load(f)
+
+                yield {"imgname": fname, "image": s.path.join(images_path,fname+'.jpeg'), "label": np.max([int(a['label'][:1]) for a in data['shapes']])}