| |
| import gradio as gr |
| from transformers import BlipProcessor, BlipForConditionalGeneration |
| from PIL import Image |
|
|
| processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base") |
| model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base") |
|
|
| def caption_image(image): |
| inputs = processor(images=image, return_tensors="pt") |
| out = model.generate(**inputs) |
| caption = processor.decode(out[0], skip_special_tokens=True) |
| return caption |
|
|
| gr.Interface(fn=caption_image, inputs=gr.Image(), outputs="text").launch() |
|
|
