plantsdataset.py

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}"

class PlantsDataset(GeneratorBasedBuilder):
    VERSION = "1.0.0"

    def _info(self):
        features = Features({
            "image": Value("string"),
            "label": Value("int64"),
        })
        return DatasetInfo(
            description="Your dataset description",
            features=features,
            supervised_keys=("image", "label"),
            homepage="Your dataset homepage",
            citation="Citation for your dataset",
        )

    def _split_generators(self, dl_manager):
        downloaded_file = dl_manager.download_and_extract(_URL)

        return [
            SplitGenerator(
                name=Split.TRAIN,
                gen_kwargs={
                    "data_folder": os.path.join(downloaded_file, "train"),
                },
            ),
            SplitGenerator(
                name=Split.TEST,
                gen_kwargs={
                    "data_folder": os.path.join(downloaded_file, "test"),
                },
            ),
        ]

    def _generate_examples(self, data_folder):
        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'])]

                        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()