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from PIL import Image | |
import requests | |
import gradio as gr | |
from transformers import BlipProcessor, BlipForConditionalGeneration | |
model_id = "Salesforce/blip-image-captioning-base" | |
model = BlipForConditionalGeneration.from_pretrained(model_id) | |
processor = BlipProcessor.from_pretrained(model_id) | |
## | |
def launch(input): | |
image = Image.open(requests.get(input, stream=True).raw).convert('RGB') | |
inputs = processor(image, return_tensors="pt") | |
out = model.generate(**inputs) | |
return processor.decode(out[0], skip_special_tokens=True) | |
iface = gr.Interface(launch, inputs="text", outputs="text") | |
iface.launch() |