| 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() |
