Spaces:
Sleeping
Sleeping
File size: 1,751 Bytes
248b38d a6ff839 248b38d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
import streamlit as st
from transformers import AutoProcessor, UdopForConditionalGeneration
from datasets import load_dataset
processor = AutoProcessor.from_pretrained("microsoft/udop-large", apply_ocr=True)
model = UdopForConditionalGeneration.from_pretrained("microsoft/udop-large")
st.title("Image Selection and Upload")
st.write("Select or upload an image to test the model.")
# Image selection
image_option = st.selectbox("Select an image:", ("Image 1", "Image 2", "Image 3"))
if image_option == "Image 1":
st.image("image1.jpg", caption="Image 1")
elif image_option == "Image 2":
st.image("image2.jpg", caption="Image 2")
elif image_option == "Image 3":
st.image("image3.jpg", caption="Image 3")
# Image upload
uploaded_file = st.file_uploader("Upload an image:", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
st.image(uploaded_file, caption="Uploaded Image")
# Model testing button
if st.button("Test Model"):
if image_option == "Image 1":
# Test the model with Image 1
st.write("Testing the model with Image 1...")
elif image_option == "Image 2":
# Test the model with Image 2
st.write("Testing the model with Image 2...")
elif image_option == "Image 3":
# Test the model with Image 3
st.write("Testing the model with Image 3...")
elif uploaded_file is not None:
# Test the model with the uploaded image
st.write("Testing the model with the uploaded image...")
else:
st.write("Please select or upload an image.")
# encoding = processor(image, question, words, boxes=boxes, return_tensors="pt")
# predicted_ids = model.generate(**encoding)
# print(processor.batch_decode(predicted_ids, skip_special_tokens=True)[0])
|