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import gradio as gr | |
# from PIL import Image | |
from transformers.utils import logging | |
from transformers import BlipForConditionalGeneration, AutoProcessor | |
from transformers import pipeline | |
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() | |
# logging.set_verbosity_error() | |
# model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base") | |
# processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base") | |
# def caption_image(image): | |
# inputs = processor(image, return_tensors="pt") | |
# out = model.generate(**inputs) | |
# caption = processor.decode(out[0], skip_special_tokens=True) | |
# return caption | |
# iface = gr.Interface(fn=caption_image, inputs=["image"], outputs="textbox") | |
# iface.launch() | |
# gr.Interface(caption_image, gr.inputs.Image(), "text").launch() | |
# gr.Interface(caption_image, image_input, caption_output).launch() | |
# import streamlit as st | |
# # from PIL import Image | |
# from transformers.utils import logging | |
# from transformers import BlipForConditionalGeneration, AutoProcessor | |
# import torch | |
# logging.set_verbosity_error() | |
# model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base") | |
# processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base") | |
# st.title("Image Captioning") | |
# uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) | |
# if uploaded_file is not None: | |
# image = Image.open(uploaded_file) | |
# st.image(image, caption="Uploaded Image", use_column_width=True) | |
# st.write("") | |
# st.write("Generating caption...") | |
# inputs = processor(image, return_tensors="pt") | |
# out = model.generate(**inputs) | |
# caption = processor.decode(out[0], skip_special_tokens=True) | |
# st.write("Caption:", caption) | |