Update plantsdataset.py

plantsdataset.py

@@ -1,31 +1,21 @@
-from datasets import DatasetInfo, Features, Value, ClassLabel, Split, SplitGenerator, GeneratorBasedBuilder, BuilderConfig
+from datasets import DatasetInfo, Features, Value, ClassLabel, Split, SplitGenerator, GeneratorBasedBuilder, BuilderConfig, Array3D
 import os
 from PIL import Image
 import matplotlib.pyplot as plt
 import numpy as np
 
-# Rest of your code...
-
-# Google Drive ID for your ZIP file
 _DRIVE_ID = "1fXgVwhdU5YGj0SPIcHxSpxkhvRh54oEH"
 _URL = f"https://drive.google.com/uc?export=download&id={_DRIVE_ID}"
 
 class PlantsDataset(GeneratorBasedBuilder):
-    class MyConfig(BuilderConfig):
-        def __init__(self, **kwargs):
-            super().__init__(**kwargs)
-
-    BUILDER_CONFIGS = [
-        MyConfig(name="plants_default", description="Default configuration for PlantsDataset"),
-    ]
-    
+    VERSION = datasets.Version("1.0.0")
     BUILDER_CONFIGS = [
-        MyConfig(name="default", description="Default configuration"),
+        BuilderConfig(name="default", version=VERSION, description="Default configuration for PlantsDataset"),
     ]
 
     def _info(self):
         features = Features({
-            "image": Value("string"),
+            "image": Array3D(dtype="uint8", shape=(None, None, 3)),  # Change to Array3D to store image arrays
             "label": ClassLabel(names=["aleo vera", "calotropis gigantea"]),
         })
         return DatasetInfo(
@@ -56,31 +46,19 @@ class PlantsDataset(GeneratorBasedBuilder):
 
     def _generate_examples(self, data_folder):
         label_names = self.info.features['label'].names
-        for label, subfolder in enumerate(label_names):
-            subfolder_path = os.path.join(data_folder, subfolder)
+        for label_name in label_names:
+            subfolder_path = os.path.join(data_folder, label_name)
+            label = label_names.index(label_name)
             for root, _, files in os.walk(subfolder_path):
                 for file_name in files:
                     file_path = os.path.join(root, file_name)
-                    if os.path.isfile(file_path):
-                        # Open the image using Pillow and convert it to an array
-                        with Image.open(file_path) as image:
-                            image_array = np.array(image)
-    
-                        # Yield the example with the image data and label
-                        yield file_path, {
-                            "image": image_array.tolist(),  # Convert array to list
-                            "label": label,
-                        }
-
-    def _display_image(self, image_path, label):
-        with Image.open(image_path) as img:
-            plt.imshow(img)
-            plt.title(f"Label: {self.info.features['label'].int2str(label)}")
-            plt.axis('off')  # Hide the axis
-            plt.show()
-
-# Create an instance of the PlantsDataset class
-plants_dataset = PlantsDataset()
-
-# Build and upload the dataset
-plants_dataset.download_and_prepare()
+                    if os.path.isfile(file_path) and file_name.lower().endswith(('.png', '.jpg', '.jpeg')):
+                        try:
+                            with Image.open(file_path) as image:
+                                image_array = np.array(image)
+                                yield file_path, {
+                                    "image": image_array,  # Keep as numpy array
+                                    "label": label,
+                                }
+                        except (IOError, OSError):
+                            print(f"Skipped file {file_path}, due to an error opening the image.")