Spaces:
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Sleeping
| from transformers import AutoProcessor,AutoModelForImageTextToText | |
| from PIL import Image | |
| import sys | |
| from exception import MyException | |
| async def image_to_text(image_path:str)->str: | |
| try: | |
| image=Image.open(image_path).convert('RGB') | |
| processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-large") | |
| model = AutoModelForImageTextToText.from_pretrained("Salesforce/blip-image-captioning-large") | |
| inputs = processor(images=image, return_tensors="pt") | |
| # Generate a caption | |
| generated_ids = model.generate(**inputs) | |
| generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0].strip() | |
| return generated_text | |
| except Exception as e: | |
| raise MyException(f"Error in image_to_text: {str(e)}") | |