Update Graptolodiea-Speciemens-Imaging.py

Graptolodiea-Speciemens-Imaging.py

@@ -12,19 +12,35 @@ from PIL import Image
 import ast
 
 _CITATION = """\
-111
-""" 
+@dataset{Xu2022graptolitespecimens
+  title = {High-resolution images of 1550 Ordovician to Silurian graptolite specimens for global correlation and shale gas exploration},
+  author = {Honghe Xu},
+  year = {2022},
+  url = {https://zenodo.org/records/6194943},
+  publisher = {Zenodo}
+}
+"""
 
 _DESCRIPTION = """\
-[Your dataset description here...]
+This dataset includes high-quality images of specimens, each meticulously tagged with taxonomic details such as suborder, infraorder, family, and genus. 
+Additionally, the dataset is enriched with crucial metadata like the geological stage, mean age value, and specific locality coordinates (longitude, latitude, and horizon). 
+References to original specimen publications are also provided, ensuring comprehensive documentation for academic rigor.
 """
 
 _HOMEPAGE = "https://zenodo.org/records/6194943"
-_license = "111"
 
-class GraptoloideaSpecimensDataset(datasets.GeneratorBasedBuilder):
-    _URL = "https://raw.githubusercontent.com/LeoZhangzaolin/photos/main/Final_GS_with_Images5.csv"
+_LICENSE = "CC BY 4.0"
+
+_URL = "https://raw.githubusercontent.com/LeoZhangzaolin/photos/main/Final_GS_with_Images5.csv"
 
+class GraptoloideaSpecimensDataset(datasets.GeneratorBasedBuilder):
+    """This dataset script retrives my processed dataset. It stands as a vital resource for researchers and enthusiasts in the field of paleontology
+    , particularly those focusing on graptolites. Its compilation not only aids in the study of these fascinating creatures but also contributes 
+    significantly to our understanding of Earth's biological and geological past.
+    """
+    _URL = _URL
+    VERSION = datasets.Version("1.1.0")
+    
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
@@ -34,17 +50,18 @@ class GraptoloideaSpecimensDataset(datasets.GeneratorBasedBuilder):
                     "Infraorder": datasets.Value("string"),
                     "Family (Subfamily)": datasets.Value("string"),
                     "Genus": datasets.Value("string"),
-                    "Tagged Species Name": datasets.Value("string"),
-                    "Image": datasets.Value("string"),
+                    "tagged species name": datasets.Value("string"),
+                    "image": datasets.Value("string"),
                     "Stage": datasets.Value("string"),
-                    "Mean Age Value": datasets.Value("float64"),
+                    "mean age value": datasets.Value("float64"),
                     "Locality (Longitude, Latitude, Horizon)": datasets.Value("string"),
-                    "Reference (Specimens Firstly Published)": datasets.Value("string"),
+                    "Reference (specimens firstly published)": datasets.Value("string"),
                 }
             ),
             supervised_keys=None,
             homepage=_HOMEPAGE,
-            citation=_CITATION,
+            license = _LICENSE,
+            citation=_CITATION
         )
 
     def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
@@ -78,7 +95,7 @@ class GraptoloideaSpecimensDataset(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, filepath):
-        """This function returns the examples from the CSV file."""
+        """This function returns the examples."""
         logging.info("generating examples from = %s", filepath)
         with open(filepath, encoding='utf-8') as f:
             reader = csv.DictReader(f)
@@ -111,20 +128,3 @@ class GraptoloideaSpecimensDataset(datasets.GeneratorBasedBuilder):
                     "Reference (specimens firstly published)": reference,
                 }
 
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