kengui's picture
Create app.py
208b01b verified
raw
history blame
653 Bytes
!pip install transformers
!pip install gradio
!pip install gradio_client
from transformers.utils import logging
import warnings
import os
import gradio as gr
from transformers import pipeline
logging.set_verbosity_error()
warnings.filterwarnings("ignore",
message="Using the model-agnostic default `max_length`")
pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
def launch(input):
out = pipe(input)
return out[0]['generated_text']
iface = gr.Interface(launch,
inputs=gr.Image(type='pil'),
outputs="text")
iface.launch()
iface.close()