Update soybean_dataset.py

soybean_dataset.py

@@ -67,9 +67,9 @@ _LICENSE = "Under a Creative Commons license"
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URL = "/content/drive/MyDrive/sta_663/soybean/dataset.csv"
 _URLs = {
-    "train" : "https://drive.google.com/file/d/1-5Tdr_OTUUfkjf_UCa5EZOjGdlW683S-/view?usp=sharing",
-    "test": "https://drive.google.com/file/d/1-2wUyuBTeesGxLuDCvxRcUPdftL-Zen9/view?usp=sharing",
-    "valid": "https://drive.google.com/file/d/1-1DeSjBY9YlfGCl7CvoU97h7eX95R1eC/view?usp=sharing"
+    "train" : "https://raw.githubusercontent.com/lisawen0707/soybean/main/train_dataset.csv",
+    "test": "https://raw.githubusercontent.com/lisawen0707/soybean/main/test_dataset.csv",
+    "valid": "https://raw.githubusercontent.com/lisawen0707/soybean/main/valid_dataset.csv"
 }
 
 # TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
@@ -136,7 +136,8 @@ class SoybeanDataset(datasets.GeneratorBasedBuilder):
 
         with open(filepath, encoding="utf-8") as f:
             data = csv.DictReader(f)
-            
+
+
             for row in data:
                 # Assuming the 'original_image' column has the full path to the image file
                 unique_id = row['unique_id']
@@ -158,6 +159,28 @@ class SoybeanDataset(datasets.GeneratorBasedBuilder):
                     # ... add other features if necessary
                 }
     
+                # for row in data:
+                # # Assuming the 'original_image' column has the full path to the image file
+                # unique_id = row['unique_id']
+                # original_image_path = row['original_image']
+                # segmentation_image_path = row['segmentation_image']
+                # sets = row['sets']
+
+                # original_image_array = self.process_image(original_image_path)
+                # segmentation_image_array = self.process_image(segmentation_image_path)
+
+                
+                # # Here you need to replace 'initial_radius', 'final_radius', 'initial_angle', 'final_angle', 'target'
+                # # with actual columns from your CSV or additional processing you need to do
+                # yield row['unique_id'], {
+                #     "unique_id": unique_id,
+                #     "sets": sets,
+                #     "original_image": original_image_array,
+                #     "segmentation_image": segmentation_image_array,
+                #     # ... add other features if necessary
+                # }
+    
+    
     
     
     
@@ -169,4 +192,38 @@ class SoybeanDataset(datasets.GeneratorBasedBuilder):
     
     
     
-    
+    #### origin
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+      urls_to_download = self._URLS
+      downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+      return [
+          datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
+          datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
+      ]
+      
+    def _generate_examples(self, filepath):
+        """This function returns the examples in the raw (text) form."""
+        logging.info("generating examples from = %s", filepath)
+        with open(filepath) as f:
+            squad = json.load(f)
+            for article in squad["data"]:
+                title = article.get("title", "").strip()
+                for paragraph in article["paragraphs"]:
+                    context = paragraph["context"].strip()
+                    for qa in paragraph["qas"]:
+                        question = qa["question"].strip()
+                        id_ = qa["id"]
+
+                        answer_starts = [answer["answer_start"] for answer in qa["answers"]]
+                        answers = [answer["text"].strip() for answer in qa["answers"]]
+
+                        # Features currently used are "context", "question", and "answers".
+                        # Others are extracted here for the ease of future expansions.
+                        yield id_, {
+                            "title": title,
+                            "context": context,
+                            "question": question,
+                            "id": id_,
+                            "answers": {"answer_start": answer_starts, "text": answers,},
+                        }