Update plantsdataset.py

plantsdataset.py

@@ -1,30 +1,20 @@
-# -*- coding: utf-8 -*-
-"""PlantsDataset
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/13QeVLQP2QGaxkGcaoMi25geoBxHQ_3rQ
-"""
-
-from datasets import Dataset, DatasetInfo, Features, Value, Split, DownloadManager, GeneratorBasedBuilder
-from datasets import SplitGenerator
-# URL for the datasethttps://drive.google.com/file/d/1fXgVwhdU5YGj0SPIcHxSpxkhvRh54oEH/view?usp=share_link
-import os
 from datasets import Dataset, DatasetInfo, Features, Value, Split, GeneratorBasedBuilder
+import matplotlib.pyplot as plt
+import random
+import os
+import cv2
 
 # Google Drive ID for your ZIP file
 _DRIVE_ID = "1fXgVwhdU5YGj0SPIcHxSpxkhvRh54oEH"
 _URL = f"https://drive.google.com/uc?export=download&id={_DRIVE_ID}"
 
-# Custom Dataset Class
 class PlantsDataset(GeneratorBasedBuilder):
     VERSION = "1.0.0"
 
     def _info(self):
         features = Features({
-            "image": Value("string"),  # Replace with the actual datatype for your image data
-            "label": Value("int64"),   # Replace with the actual datatype for your label data
+            "image": Value("string"),
+            "label": Value("int64"),
         })
         return DatasetInfo(
             description="Your dataset description",
@@ -53,23 +43,37 @@ class PlantsDataset(GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, data_folder):
-      for label, subfolder in enumerate(["gigantic", "small"]):
-          subfolder_path = os.path.join(data_folder, subfolder)
-          for root, _, files in os.walk(subfolder_path):
-              for file_name in files:
-                  file_path = os.path.join(root, file_name)
+        displayed_index = -1
+
+        for label, subfolder in enumerate(["aleo vera", "calotropis gigantea"]):
+            subfolder_path = os.path.join(data_folder, subfolder)
+            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):
+                        # Display the image
+                        displayed_index = (displayed_index + 1) % (len(self._datasets['train']) + len(self._datasets['test']))
+                        if displayed_index < len(self._datasets['train']):
+                            subset_name = 'train'
+                            example = self._datasets[subset_name][displayed_index]
+                        else:
+                            subset_name = 'test'
+                            example = self._datasets[subset_name][displayed_index - len(self._datasets['train'])]
 
-                  # Check if file_path is a file, not a directory
-                  if os.path.isfile(file_path):
-                      # Yield the example
-                      yield {
-                          "image": file_path,
-                          "label": label,
-                      }
+                        image = cv2.imread(example['image'])
+                        plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+                        plt.title(f"Subset: {subset_name}, Label: {example['label']}")
+                        plt.show()
 
+                        # Yield the example
+                        yield {
+                            "image": file_path,
+                            "label": label,
+                        }
 
 # Create an instance of the PlantsDataset class
 plants_dataset = PlantsDataset()
 
 # Build and upload the dataset
-plants_dataset.download_and_prepare()
+plants_dataset.download_and_prepare()