vikaso001/phi2-rag-api

1import streamlit as st2from PIL import Image3import tempfile4from preprocessing.process import modify_image5from model.loader import ImageProcessor6from text_classifier.classifier import extract_medical_info, extract_and_save_medical_info7from search.extractor import get_medication_details8import os9 10# ✅ Must be the first Streamlit command11st.set_page_config(page_title="Medical Image Analyzer", page_icon="🔍", layout="wide")12 13# Title14st.title("Medical Image Text Analyzer")15 16# Image upload widget17uploaded_image = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg", "gif", "webp"])18 19# If an image is uploaded20if uploaded_image:21    # Show the uploaded image22    image = Image.open(uploaded_image)23    st.image(image, caption="Uploaded Image", use_column_width=True)24 25    # Process the image when the button is clicked26    if st.button("Analyze Image"):27        try:28            # Save the image temporarily to disk29            with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_file:30                image.save(temp_file.name)31 32            # Image processing (preprocessing steps: grayscale, sharpen, enhance contrast)33            processed_image = modify_image(temp_file.name)34 35            if processed_image is not None:36                st.image(processed_image, caption="Processed Image", use_column_width=True)37 38                # Use the loader to analyze the image and get the markdown content39                processor = ImageProcessor()40                markdown_result = processor.analyze_image(image_path=temp_file.name)41 42                # Extract the text data from the markdown result43                medical_info = extract_medical_info(markdown_result)44 45                # Optional: Save to file46                extract_and_save_medical_info(markdown_result)47 48                # Display the extracted medical information49                st.subheader("Extracted Medical Information")50                if isinstance(medical_info, dict):51                    st.json(medical_info)52 53                    # Get medication details (with fuzzy matching)54                    medications = medical_info.get("medications", [])55                    medication_details_df = get_medication_details(medications)56 57 58                # Display the extracted medical information59                st.subheader("Extracted Medical Information")60                if isinstance(medical_info, dict):61                    st.json(medical_info)62 63                    # Get medication details (with fuzzy matching)64                    medications = medical_info.get("medications", [])65                    medication_details_df = get_medication_details(medications)66 67                    # Display the medication details as a table68                    st.subheader("Medication Details")69 70                    # Loop over each medication and render it in a styled box71                    for _, row in medication_details_df.iterrows():72                        st.markdown(73                            f"""74                            <div style="color:black; border: 1px solid #ccc; border-radius: 10px; padding: 15px; margin-bottom: 20px; background-color: #f9f9f9;">75                                <h4 style="color: #2c3e50;">🩺 {row['Name']}</h4>76                                <p style="color: #2c3e50;"><strong>Contains:</strong> {row['Contains']}</p>77                                <p style="color: #2c3e50;"><strong>How to Use:</strong> {row['How to Use']}</p>78                                <p style="color: #2c3e50;"><strong>Advice:</strong><br>{row['Advice']}</p>79                                <p style="color: #2c3e50;"><a href="{row['Link']}" target="_blank">🔗 More Info</a></p>80                            </div>81                            """,82                            unsafe_allow_html=True83                        )84                        85                else:86                    st.error("Failed to extract medical information.")87                # ✅ Cleanup88                if os.path.exists(temp_file.name):89                    os.remove(temp_file.name)90        except Exception as e:91            st.error(f"Error analyzing image: {str(e)}")92 93