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import gradio as gr
from transformers import BlipForConditionalGeneration
from transformers import AutoProcessor
model = BlipForConditionalGeneration.from_pretrained(
"Salesforce/blip-image-captioning-base")
processor = AutoProcessor.from_pretrained(
"Salesforce/blip-image-captioning-base")
def image_caption(input):
inputs = processor(input, return_tensors="pt")
out = model.generate(**inputs)
return processor.decode(out[0], skip_special_tokens = True)
iface = gr.Interface(fn = image_caption,
inputs = gr.Image(type='pil'),
outputs = "text")
iface.launch() |