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import streamlit as st |
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from transformers import BlipProcessor, BlipForConditionalGeneration |
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from PIL import Image |
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import torch |
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st.title("AI Image Caption Generator") |
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st.write("Upload an image and get a caption generated by an AI model!") |
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uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"]) |
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if uploaded_file: |
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image = Image.open(uploaded_file).convert('RGB') |
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st.image(image, caption="Uploaded Image", use_column_width=True) |
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st.write("Generating caption...") |
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processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base") |
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model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base") |
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inputs = processor(image, return_tensors="pt") |
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out = model.generate(**inputs) |
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caption = processor.decode(out[0], skip_special_tokens=True) |
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st.success(f"📝 Caption: {caption}") |
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