Spaces:
Sleeping
Sleeping
File size: 1,136 Bytes
02fa2f8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 |
import requests
from PIL import Image
from transformers import BlipProcessor, BlipForConditionalGeneration
# Load the models and processor
processor_base = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model_base = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
processor_large = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
model_large = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large")
# Define the function for unconditional image captioning
def caption_image_unconditional(image):
inputs = processor_base(image, return_tensors="pt")
outputs = model_base.generate(**inputs)
caption = processor_base.decode(outputs[0], skip_special_tokens=True)
return caption
# Define the function for conditional image captioning
def caption_image_conditional(image, text):
inputs = processor_large(image, text, return_tensors="pt")
outputs = model_large.generate(**inputs)
caption = processor_large.decode(outputs[0], skip_special_tokens=True)
return caption
|