Update app.py
Browse files
app.py
CHANGED
@@ -1,20 +1,29 @@
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import streamlit as st # Don't forget to include `streamlit` in your `requirements.txt` file to ensure the app runs properly on Hugging Face Spaces.
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from PIL import Image # Ensure the `pillow` library is included in your `requirements.txt`.
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import torch # Since PyTorch is required for this app, specify the appropriate version of `torch` in `requirements.txt` based on compatibility with the model.
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import os
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def load_model():
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"""Load PaliGemma2 model and processor with Hugging Face token."""
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token = os.getenv("HUGGINGFACEHUB_API_TOKEN") # Retrieve token from environment variable
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if not token:
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raise ValueError("Hugging Face API token not found. Please set it in the environment variables.")
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model
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return processor, model
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def process_image(image, processor, model):
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"""Extract text from image using PaliGemma2."""
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# Preprocess the image
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inputs = processor(images=image, return_tensors="pt")
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@@ -29,7 +38,7 @@ def main():
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# Set page configuration
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st.set_page_config(page_title="Text Reading with PaliGemma2", layout="centered")
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st.title("Text Reading from Images using PaliGemma2")
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# Load model and processor
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with st.spinner("Loading PaliGemma2 model... This may take a few moments."):
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try:
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@@ -38,10 +47,10 @@ def main():
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except ValueError as e:
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st.error(str(e))
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st.stop()
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# User input: upload image
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uploaded_image = st.file_uploader("Upload an image containing text", type=["png", "jpg", "jpeg"])
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if uploaded_image is not None:
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# Display uploaded image
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image = Image.open(uploaded_image)
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@@ -54,10 +63,10 @@ def main():
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st.success("Text extraction complete!")
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st.subheader("Extracted Text")
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st.write(extracted_text)
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# Footer
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st.markdown("---")
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st.markdown("**Built with [PaliGemma2](https://huggingface.co/google/paligemma2) and Streamlit**")
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if __name__ == "__main__":
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main()
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import streamlit as st # Don't forget to include `streamlit` in your `requirements.txt` file to ensure the app runs properly on Hugging Face Spaces.
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from transformers import AutoProcessor, AutoModelForImageTextToText # Updated imports to reflect changes
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from PIL import Image # Ensure the `pillow` library is included in your `requirements.txt`.
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+
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import torch # Since PyTorch is required for this app, specify the appropriate version of `torch` in `requirements.txt` based on compatibility with the model.
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import os
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def load_model():
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"""Load PaliGemma2 model and processor with Hugging Face token."""
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token = os.getenv("HUGGINGFACEHUB_API_TOKEN") # Retrieve token from environment variable
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if not token:
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raise ValueError("Hugging Face API token not found. Please set it in the environment variables.")
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# Load the processor and model using the correct identifier
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processor = AutoProcessor.from_pretrained("google/paligemma2-3b-pt-224", use_auth_token=token)
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model = AutoModelForImageTextToText.from_pretrained("google/paligemma2-3b-pt-224", use_auth_token=token)
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return processor, model
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def process_image(image, processor, model):
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"""Extract text from image using PaliGemma2."""
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# Preprocess the image
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inputs = processor(images=image, return_tensors="pt")
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# Set page configuration
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st.set_page_config(page_title="Text Reading with PaliGemma2", layout="centered")
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st.title("Text Reading from Images using PaliGemma2")
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# Load model and processor
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with st.spinner("Loading PaliGemma2 model... This may take a few moments."):
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try:
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except ValueError as e:
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st.error(str(e))
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st.stop()
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# User input: upload image
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uploaded_image = st.file_uploader("Upload an image containing text", type=["png", "jpg", "jpeg"])
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if uploaded_image is not None:
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# Display uploaded image
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image = Image.open(uploaded_image)
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st.success("Text extraction complete!")
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st.subheader("Extracted Text")
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st.write(extracted_text)
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# Footer
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st.markdown("---")
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st.markdown("**Built with [PaliGemma2](https://huggingface.co/google/paligemma2-3b-pt-224) and Streamlit**")
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if __name__ == "__main__":
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main()
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