| | from PIL import Image |
| | from transformers import BlipForConditionalGeneration, BlipProcessor |
| |
|
| | processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large") |
| | model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large") |
| |
|
| | def extract_image_details(image): |
| | inputs = processor(images=image, return_tensors="pt") |
| |
|
| | generated_ids = model.generate( |
| | pixel_values=inputs["pixel_values"], |
| | max_length=50, |
| | num_beams=5, |
| | do_sample=False |
| | ) |
| | generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0] |
| | print(f"BLIP Model Description: {generated_text}") |
| | return generated_text |
| |
|