Spaces:
Runtime error
Runtime error
| from transformers import pipeline | |
| import streamlit as st | |
| from PIL import Image | |
| import requests | |
| from io import BytesIO | |
| # Initialize the pipeline | |
| image_to_text = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning") | |
| st.title('Image Captioning Application') | |
| # Function to load images from URL | |
| def load_image_from_url(url): | |
| try: | |
| response = requests.get(url) | |
| img = Image.open(BytesIO(response.content)) | |
| return img | |
| except Exception as e: | |
| st.error(f"Error loading image from URL: {e}") | |
| return None | |
| # User option to select input type: Upload or URL | |
| input_type = st.radio("Select input type:", ("Upload Image", "Image URL", "Text")) | |
| if input_type == "Upload Image": | |
| 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) | |
| elif input_type == "Image URL": | |
| image_url = st.text_input("Enter the image URL here:", "") | |
| if image_url: | |
| image = load_image_from_url(image_url) | |
| if image: | |
| st.image(image, caption='Image from URL', use_column_width=True) | |
| elif input_type == "Text": | |
| text_input = st.text_input("Enter text here:", "") | |
| if text_input: | |
| st.image(image, caption='Image from URL', use_column_width=True) | |
| # Generate caption button | |
| if st.button('Generate Caption'): | |
| if not image: | |
| if not text_input: | |
| st.warning("Please upload an image, enter an image URL or input text") | |
| else: | |
| result = text_input | |
| else: | |
| with st.spinner("Generating caption..."): | |
| # Process the image and generate caption | |
| if input_type == "Upload Image": | |
| # Save the uploaded image to a temporary file to pass its path to the model | |
| with open("temp_image.jpg", "wb") as f: | |
| f.write(uploaded_file.getbuffer()) | |
| result = image_to_text("temp_image.jpg") | |
| elif input_type == "Image URL" and image_url: | |
| result = image_to_text(image_url) | |
| if result: | |
| generated_text = result[0]['generated_text'] | |
| st.success(f'Generated Caption: {generated_text}') | |
| else: | |
| st.error("Failed to generate caption.") | |