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| import streamlit as st | |
| from PIL import Image | |
| import io | |
| from dotenv import load_dotenv | |
| import os | |
| import openai | |
| from openai import OpenAI | |
| # Google Cloud Vision | |
| from google.cloud import vision | |
| # Load environment variables | |
| load_dotenv() | |
| # Set Google Cloud credentials in environment | |
| service_account_path = os.getenv("GOOGLE_APPLICATION_CREDENTIALS") | |
| os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = r'gcv-new-project-dd6ed833cc91.json' | |
| # Initialize Google Vision client | |
| vision_client = vision.ImageAnnotatorClient() | |
| def extract_text_with_google_vision_api(image): | |
| """Extract structured text from image using Google Cloud Vision API, with additional formatting based on bounding box analysis.""" | |
| import io | |
| from google.cloud import vision | |
| vision_client = vision.ImageAnnotatorClient() | |
| img_byte_arr = io.BytesIO() | |
| image.save(img_byte_arr, format=image.format) | |
| image_bytes = img_byte_arr.getvalue() | |
| image = vision.Image(content=image_bytes) | |
| response = vision_client.document_text_detection(image=image) | |
| structured_texts = [] | |
| for page in response.full_text_annotation.pages: | |
| for block in page.blocks: | |
| block_texts = [] | |
| last_paragraph_bottom = None # Store the bottom position of the last paragraph to compare spacing | |
| for paragraph in block.paragraphs: | |
| paragraph_text = ' '.join([''.join([symbol.text for symbol in word.symbols]) for word in paragraph.words]) | |
| paragraph_text = paragraph_text.strip() | |
| # Example for analyzing bounding box position and size (simplified) | |
| paragraph_bounds = paragraph.bounding_box | |
| top_left = paragraph_bounds.vertices[0] # Example vertex | |
| if last_paragraph_bottom is not None and (top_left.y - last_paragraph_bottom) > 10: | |
| # Add additional break if the spacing exceeds some threshold | |
| block_texts.append("") # This adds an extra line break to indicate a significant separation | |
| # Update last_paragraph_bottom to the current paragraph's bottom position | |
| last_paragraph_bottom = paragraph_bounds.vertices[2].y # Assuming 0 is top-left and going clockwise | |
| if len(paragraph_text.split()) > 2: | |
| block_texts.append(paragraph_text) | |
| if block_texts: | |
| structured_texts.append('\n'.join(block_texts)) | |
| if structured_texts: | |
| return '\n\n'.join(structured_texts) | |
| else: | |
| return "No structured text found." | |
| def main(): | |
| st.title("Article Extraction") | |
| uploaded_file = st.file_uploader("Upload 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) | |
| extracted_text = extract_text_with_google_vision_api(image) | |
| st.success("Analysis completed successfully!") | |
| st.header("Extracted Text:") | |
| st.write(extracted_text if extracted_text else "No text detected.") | |
| if __name__ == "__main__": | |
| main() |