| import os |
| import json |
| import datasets |
| from datasets import Dataset, DatasetDict, load_dataset, Features, Value, Image, ClassLabel |
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| image_root_dir = "./" |
| train_jsonl_file_path = "arabic_memes_categorization_train.jsonl" |
| dev_jsonl_file_path = "arabic_memes_categorization_dev.jsonl" |
| test_jsonl_file_path = "arabic_memes_categorization_test.jsonl" |
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| |
| def load_armeme_split(jsonl_file_path, image_root_dir): |
| texts = [] |
| images = [] |
| ids=[] |
| class_labels=[] |
| image_file_paths = [] |
| |
| |
| with open(jsonl_file_path, 'r') as f: |
| for line in f: |
| item = json.loads(line) |
| ids.append(item['id']) |
| texts.append(item['text']) |
| image_file_path = os.path.join(image_root_dir, item['img_path']) |
| images.append(image_file_path) |
| image_file_paths.append(image_file_path) |
| class_labels.append(item['class_label']) |
| |
| |
| data_dict = { |
| 'id':ids, |
| 'text': texts, |
| 'image': images, |
| 'img_path': image_file_paths, |
| 'class_label': class_labels |
| } |
| |
| |
| features = Features({ |
| 'id': Value('string'), |
| 'text': Value('string'), |
| 'image': Image(), |
| 'img_path': Value('string'), |
| 'class_label': ClassLabel(names=['not_propaganda','propaganda','not-meme','other']) |
| }) |
| |
| |
| dataset = Dataset.from_dict(data_dict, features=features) |
| return dataset |
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| |
| train_dataset = load_armeme_split(train_jsonl_file_path, image_root_dir) |
| dev_dataset = load_armeme_split(dev_jsonl_file_path, image_root_dir) |
| test_dataset = load_armeme_split(test_jsonl_file_path, image_root_dir) |
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| |
| dataset_dict = DatasetDict({ |
| 'train': train_dataset, |
| 'dev': dev_dataset, |
| 'test': test_dataset |
| }) |
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| |
| dataset_dict.push_to_hub("QCRI/ArMeme") |
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