import streamlit as st from PIL import Image, ImageOps import pandas as pd import numpy as np from invoice import extract_data, extract_tables, INVOICE import cv2 def process_image(lang, to_be_extracted, input_image): data = extract_data(lang, to_be_extracted, input_image) return data def main(): st.title("Image Processing App") st.write("Upload an image and click the 'Process Image' button to process it.") uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png","webp"]) if uploaded_image is not None: # Display the uploaded image st.image(uploaded_image, caption="Uploaded Image", use_column_width=True) lang = st.selectbox("Select Language", ["french", "english", "arabic"]) # UI for adding elements to extract list st.write("Add elements to extract:") extract_input = st.text_input("Add elements") extract_list = st.session_state.get("extract_list", INVOICE) if extract_input: extract_list.append(extract_input.strip()) st.session_state["extract_list"] = extract_list # Display the extract list as chips st.write("Elements to extract:") for item in extract_list: st.write(f"`{item}`", unsafe_allow_html=True) if st.button("Extract information"): pil_image = Image.open(uploaded_image).convert('RGB') numpy_image = np.array(pil_image) image_info = process_image(lang, extract_list, numpy_image) df = pd.DataFrame(list(image_info.items()), columns=["Field", "Value"]) st.write("Extracted information:") st.dataframe(df) if st.button("Extract Tables"): df = pd.DataFrame([]) csv = df.to_csv(index=False, header=False) st.download_button(label="Download CSV", data=csv, file_name='data.csv', mime='text/csv') else: st.session_state['extract_list'] = INVOICE if __name__ == "__main__": main()