Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
Tags:
art
License:
| import pandas as pd | |
| from datasets import Dataset, DatasetDict, concatenate_datasets | |
| import os | |
| def load_data(csv_file): | |
| df = pd.read_csv(csv_file) | |
| # Update the image_path column to include the full path | |
| df['label'] = df['label'].astype(int) | |
| dataset = Dataset.from_pandas(df) | |
| return dataset | |
| def load_dataset(): | |
| # Define CSV files | |
| train_csv = 'train_labels.csv' | |
| test_csv = 'test_labels.csv' | |
| # Load datasets | |
| train_dataset = load_data(train_csv) | |
| # Combine datasets for training | |
| test_dataset = load_data(test_csv) | |
| # Create DatasetDict | |
| dataset_dict = DatasetDict({ | |
| 'train': train_dataset, | |
| 'test': test_dataset | |
| }) | |
| return dataset_dict | |
| if __name__ == "__main__": | |
| dataset = load_dataset() | |
| print(dataset) | |