| """ |
| Example script for using the dots.ocr Space via API |
| |
| Requirements: |
| pip install gradio_client |
| |
| Usage: |
| python api_example.py --image path/to/image.jpg |
| """ |
|
|
| import argparse |
| from gradio_client import Client |
|
|
| def main(): |
| parser = argparse.ArgumentParser(description='Process document with dots.ocr API') |
| parser.add_argument('--image', required=True, help='Path to image file') |
| parser.add_argument('--space-url', default='YOUR_SPACE_URL_HERE', |
| help='Hugging Face Space URL') |
| parser.add_argument('--prompt-type', default='Full Layout + OCR (English)', |
| choices=['Full Layout + OCR (English)', 'OCR Only', |
| 'Layout Detection Only', 'Custom'], |
| help='Type of processing to perform') |
| parser.add_argument('--custom-prompt', default='', |
| help='Custom prompt (only used if prompt-type is Custom)') |
| |
| args = parser.parse_args() |
| |
| print(f"Connecting to Space: {args.space_url}") |
| client = Client(args.space_url) |
| |
| print(f"Processing image: {args.image}") |
| print(f"Prompt type: {args.prompt_type}") |
| |
| result = client.predict( |
| image=args.image, |
| prompt_type=args.prompt_type, |
| custom_prompt=args.custom_prompt, |
| api_name="/predict" |
| ) |
| |
| print("\n" + "="*80) |
| print("RESULT:") |
| print("="*80) |
| print(result) |
| |
| |
| output_file = args.image.rsplit('.', 1)[0] + '_ocr_result.txt' |
| with open(output_file, 'w', encoding='utf-8') as f: |
| f.write(result) |
| print(f"\nResult saved to: {output_file}") |
|
|
| if __name__ == "__main__": |
| main() |
|
|
|
|
