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| import streamlit as st | |
| from PIL import Image, ImageChops | |
| import io | |
| import numpy as np | |
| # Check if OpenCV is installed | |
| try: | |
| import cv2 | |
| OPENCV_AVAILABLE = True | |
| except ImportError: | |
| OPENCV_AVAILABLE = False | |
| # Function to perform image search (placeholder) | |
| def search_image(image): | |
| # Placeholder function for image search | |
| return { | |
| "matches": [ | |
| {"source": "Social Media A", "url": "https://example.com/match1"}, | |
| {"source": "Public Dataset B", "url": "https://example.com/match2"}, | |
| ] | |
| } | |
| # Function to save results to user profile | |
| def save_to_profile(results, user_profile): | |
| if "search_history" not in user_profile: | |
| user_profile["search_history"] = [] | |
| user_profile["search_history"].append(results) | |
| # Function to compare two images using OpenCV (if available) | |
| def compare_images_opencv(image1, image2): | |
| # Convert images to grayscale | |
| img1 = cv2.cvtColor(np.array(image1), cv2.COLOR_RGB2GRAY) | |
| img2 = cv2.cvtColor(np.array(image2), cv2.COLOR_RGB2GRAY) | |
| # Initialize ORB detector | |
| orb = cv2.ORB_create() | |
| # Detect keypoints and descriptors | |
| kp1, des1 = orb.detectAndCompute(img1, None) | |
| kp2, des2 = orb.detectAndCompute(img2, None) | |
| # Use BFMatcher to match descriptors | |
| bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True) | |
| matches = bf.match(des1, des2) | |
| # Sort matches by distance (lower is better) | |
| matches = sorted(matches, key=lambda x: x.distance) | |
| # Calculate similarity percentage | |
| similarity = (len(matches) / min(len(kp1), len(kp2))) * 100 | |
| return similarity, matches | |
| # Function to compare two images using pixel-based method (fallback) | |
| def compare_images_pixel(image1, image2): | |
| # Resize images to the same size | |
| image1 = image1.resize((256, 256)) | |
| image2 = image2.resize((256, 256)) | |
| # Calculate the difference between the two images | |
| diff = ImageChops.difference(image1, image2) | |
| # Calculate the similarity percentage | |
| diff_pixels = sum(diff.convert("L").point(lambda x: 255 if x > 0 else 0).getdata()) | |
| total_pixels = 256 * 256 | |
| similarity = 100 - (diff_pixels / total_pixels) * 100 | |
| return similarity | |
| # Streamlit app | |
| def main(): | |
| # Sidebar with navigation | |
| st.sidebar.title("Navigation") | |
| page = st.sidebar.radio("Go to", ["Home", "Compare Photos", "About Us", "Help"]) | |
| if page == "Home": | |
| st.title("Image Cross-Check App") | |
| st.write("Upload an image to cross-check it against social media and public datasets.") | |
| # File uploader | |
| uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file is not None: | |
| # Display the uploaded image | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption='Uploaded Image.', use_container_width=True) | |
| # Convert image to bytes | |
| img_byte_arr = io.BytesIO() | |
| image.save(img_byte_arr, format='PNG') | |
| img_byte_arr = img_byte_arr.getvalue() | |
| # Perform image search | |
| if st.button("Search"): | |
| with st.spinner("Searching for matches..."): | |
| results = search_image(img_byte_arr) | |
| if results["matches"]: | |
| st.success("Found matches!") | |
| for match in results["matches"]: | |
| st.write(f"Source: {match['source']}") | |
| st.write(f"URL: {match['url']}") | |
| # Save results to user profile | |
| if "user_profile" not in st.session_state: | |
| st.session_state.user_profile = {} | |
| save_to_profile(results, st.session_state.user_profile) | |
| st.success("Results saved to your profile!") | |
| else: | |
| st.warning("No matches found.") | |
| elif page == "Compare Photos": | |
| st.title("Compare Photos") | |
| st.write("Upload two images to compare their similarity.") | |
| # Upload first image | |
| uploaded_file1 = st.file_uploader("Choose the first image...", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file1 is not None: | |
| image1 = Image.open(uploaded_file1) | |
| st.image(image1, caption='First Image.', use_container_width=True) | |
| # Upload second image | |
| uploaded_file2 = st.file_uploader("Choose the second image...", type=["jpg", "jpeg", "png"]) | |
| if uploaded_file2 is not None: | |
| image2 = Image.open(uploaded_file2) | |
| st.image(image2, caption='Second Image.', use_container_width=True) | |
| # Compare images | |
| if uploaded_file1 is not None and uploaded_file2 is not None: | |
| if st.button("Compare"): | |
| with st.spinner("Comparing images..."): | |
| if OPENCV_AVAILABLE: | |
| similarity, _ = compare_images_opencv(image1, image2) | |
| else: | |
| similarity = compare_images_pixel(image1, image2) | |
| st.success(f"Similarity: {similarity:.2f}%") | |
| elif page == "About Us": | |
| st.title("About Us") | |
| st.write(""" | |
| Welcome to **Image Cross-Check App**! | |
| We are a team of developers passionate about creating tools that help you explore the digital world. | |
| Our app allows you to upload an image and cross-check it against social media platforms and public datasets. | |
| Feel free to reach out to us for feedback or suggestions! | |
| """) | |
| elif page == "Help": | |
| st.title("Help") | |
| st.write(""" | |
| ### How to Use the App: | |
| 1. **Upload an Image**: Click on the "Choose an image" button to upload a JPG, JPEG, or PNG file. | |
| 2. **Search**: Click the "Search" button to cross-check the image against social media and public datasets. | |
| 3. **View Results**: If matches are found, they will be displayed on the screen. | |
| 4. **Save Results**: The results are automatically saved to your profile for future reference. | |
| ### Compare Photos: | |
| - Upload two images and click "Compare" to calculate their similarity percentage. | |
| ### Troubleshooting: | |
| - If the app is not working, ensure you have a stable internet connection. | |
| - Supported image formats are JPG, JPEG, and PNG. | |
| - For further assistance, contact us at [email protected]. | |
| """) | |
| # Display user profile and search history | |
| if "user_profile" in st.session_state and st.session_state.user_profile.get("search_history"): | |
| st.sidebar.title("Your Profile") | |
| st.sidebar.write("### Search History") | |
| for i, search in enumerate(st.session_state.user_profile["search_history"]): | |
| st.sidebar.write(f"**Search {i+1}**") | |
| for match in search["matches"]: | |
| st.sidebar.write(f"- {match['source']}: {match['url']}") | |
| if __name__ == "__main__": | |
| main() |