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import requests
import io
import json
import datasets
import huggingface_hub

huggingface_hub.login(HF_TOKEN)
ds = datasets.load_dataset('kahua-ml/serial_number_dataset')['train']

headers = {
    'accept': 'application/json',
}

# Convert PIL Image to bytes
image_buffer = io.BytesIO()
ds[0]['image'].save(image_buffer, format='JPEG')
image_buffer.seek(0)

fields = [
    {"field_mapping":"serial_number","field_name":"serial_number","field_type":"text"},
]

files = {
    'file': ('image.jpg', image_buffer, 'image/jpeg'),
    'input': (None, '{"domain_id":"domain456","fields":' + json.dumps(fields) + ',"user_id":"user123"}'),
}

response = requests.post(
    AZURE_URL,
    headers=headers,
    files=files,
)

dataset_info: features: - name: image dtype: image - name: serial_number dtype: string splits: - name: train num_bytes: 8858770.0 num_examples: 61 download_size: 8670997 dataset_size: 8858770.0 configs: - config_name: default data_files: - split: train path: data/train-*

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