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parquet_push_to_hub.py

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+import io
+import os
+import datasets
+import traceback
+
+from PIL import Image
+from datasets import Features, Dataset
+
+def create_features():
+    features = Features(
+        {
+            'image': datasets.Image(),
+            "type": datasets.Value("string"),
+        }
+    )
+    return features
+
+def image_to_bytes(image_path):
+    image = Image.open(image_path)
+
+    image_data = io.BytesIO()
+    image.save(image_data, format='PNG')
+
+    img_data = image_data.getvalue()
+
+    return img_data
+
+def main():
+    current_directory = os.path.dirname(os.path.realpath(__file__))
+    
+    files_folder = 'files'
+    files_folder_path = os.path.join(current_directory, files_folder)
+
+    dataset_dict = {
+        'image': [],
+        "type": [],
+    }
+    
+    for root, dirs, files in os.walk(files_folder_path):
+        for file in files:
+
+            if file.lower().endswith(('.jpg', '.jpeg')):
+                file_path = os.path.join(root, file)
+                img_data = image_to_bytes(file_path)
+                dataset_dict['image'].append(img_data)
+                dataset_dict['type'].append(os.path.basename(root))
+
+
+    # print('dataset_dict', dataset_dict)
+    # print('features', create_features())
+
+    try:
+        dataset = Dataset.from_dict(dataset_dict, features=create_features())
+    except Exception as e:
+        traceback.print_exc()
+        # print(e)
+
+
+    os.environ["HF_HOME"] = "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"
+
+    dataset.push_to_hub('TrainingDataPro/chest-x-rays')
+
+
+if __name__ == "__main__":
+    main()