caption_generation.py

import torch
from transformers import BlipProcessor, BlipForConditionalGeneration

# Load the image captioning model and processor from the pretrained model
processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base",torch_dtype=torch.float16).to("mps")


# Generate captions for an input image
def generate_caption(pil_image):
    global previous_caption
    try:
        inputs = processor(pil_image, return_tensors="pt").to("mps", torch.float16)
        out = model.generate(**inputs)
        caption = processor.decode(out[0], skip_special_tokens=True)
        previous_caption = caption
        return caption
    except:
        return "Unable to process image."