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| import streamlit as st | |
| from rembg import remove | |
| from PIL import Image | |
| from io import BytesIO | |
| import numpy as np | |
| import base64 | |
| import random | |
| import cv2 | |
| import requests | |
| from bs4 import BeautifulSoup | |
| st.set_page_config(page_title="ImageMagic - Your Image Processing Companion") | |
| MAX_FILE_SIZE = 5 * 1024 * 1024 | |
| # Function to remove background using rembg library | |
| def remove_background(image): | |
| return remove(image) | |
| # Function to convert image to pencil sketch | |
| def convert_to_pencil_sketch(image): | |
| gray_img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
| invert = cv2.bitwise_not(gray_img) | |
| blur = cv2.GaussianBlur(invert, (111, 111), 0) | |
| invertedblur = cv2.bitwise_not(blur) | |
| sketch = cv2.divide(gray_img, invertedblur, scale=256.0) | |
| sketch_image = Image.fromarray(sketch) | |
| return sketch_image | |
| # Function to convert image to byte format for download | |
| def convert_image(img): | |
| buf = BytesIO() | |
| img.save(buf, format="PNG") | |
| byte_im = buf.getvalue() | |
| return byte_im | |
| # Function to process uploaded image based on selected action | |
| def process_image(upload, action): | |
| image = Image.open(upload) | |
| coli = st.columns(5) | |
| with coli[0]: | |
| st.image(image, caption="Original Image", width=300) | |
| with coli[3]: | |
| if action == "Remove Background": | |
| result = remove_background(image) | |
| st.image(result, caption="Background Removed", width=300) | |
| elif action == "Convert to Pencil Sketch": | |
| result = convert_to_pencil_sketch(cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)) | |
| st.image(result, caption="Pencil Sketch", width=300) | |
| st.markdown(get_image_download_link(result), unsafe_allow_html=True) | |
| # Function to generate download link for processed image | |
| def get_image_download_link(img, filename="result.png"): | |
| """ | |
| Generates a download link for the given image. | |
| Parameters: | |
| img (PIL.Image.Image): The image to be downloaded. | |
| filename (str): The filename to be used when downloading the image. | |
| Returns: | |
| str: The HTML string representing the download link. | |
| """ | |
| buffered = BytesIO() | |
| img.save(buffered, format="PNG") | |
| img_str = base64.b64encode(buffered.getvalue()).decode() | |
| href = f'<a href="data:image/png;base64,{img_str}" download="{filename}">Download Image</a>' | |
| return href | |
| def search_unsplash_images(query): | |
| try: | |
| # Send a request to Unsplash with the search query | |
| url = f"https://unsplash.com/s/photos/{query}" | |
| response = requests.get(url) | |
| response.raise_for_status() # Raise an exception for bad status codes | |
| # Parse the HTML content | |
| soup = BeautifulSoup(response.text, 'html.parser') | |
| # Extract image URLs from the parsed HTML | |
| image_urls = [img['src'] for img in soup.find_all('img') if img.get('src')] | |
| image_urls = image_urls[:40] | |
| random.shuffle(image_urls) | |
| # Display the images in columns with three images per column | |
| num_columns = 3 | |
| images_per_column = len(image_urls) // num_columns | |
| for i in range(num_columns): | |
| col = st.columns(num_columns) | |
| start_index = i * images_per_column | |
| end_index = (i + 1) * images_per_column | |
| for j, image_url in enumerate(image_urls[start_index:end_index], start=start_index): | |
| # Download the image | |
| image_data = requests.get(image_url).content | |
| image = Image.open(BytesIO(image_data)) | |
| # Display the image | |
| col[j % num_columns].image(image, use_column_width=True) | |
| except requests.exceptions.RequestException as e: | |
| st.warning(f"Image Not Show Try Again ") | |
| # App description | |
| st.title("🎉Welcome to ImageMagic") | |
| st.write(""" | |
| ✨ImageMagic is a versatile image processing application🚀 that simplifies common image editing tasks. | |
| Upload an image and choose from the available options to enhance your images effortlessly⚡! | |
| """) | |
| # Sidebar for options | |
| st.sidebar.title("Options") | |
| selected_option = st.sidebar.radio("Select an option", ("Home", "Remove Background", "Convert to Pencil Sketch", "Search image", "README.md")) | |
| # Display README content within the Options section | |
| if selected_option == "README.md": | |
| st.title("README") | |
| readme_content = """ | |
| # ImageMagic | |
| ## Overview | |
| ImageMagic is a powerful image processing application that allows users to enhance their images with ease. Whether you want to remove backgrounds or create stunning pencil sketches, ImageMagic has you covered. This app offers a simple and intuitive interface, making it accessible to users of all skill levels. | |
| ## Features | |
| - **Background Removal:** Effortlessly remove backgrounds from images to isolate subjects and create stunning compositions. | |
| - **Pencil Sketch Conversion:** Transform your images into beautiful pencil sketches with just a click of a button. | |
| - **Upload and Download:** Easily upload your images for processing and download the results to your device. | |
| ## Usage | |
| 1. **Upload Image:** Select an image file (supported formats include PNG, JPG, and JPEG) by clicking on the "Upload an image" button. | |
| 2. **Select Action:** Choose from the available options in the sidebar to either remove the background or convert the image to a pencil sketch. | |
| 3. **View Results:** The processed image will be displayed in the main window, allowing you to preview the changes. | |
| 4. **Download:** Once you're satisfied with the result, you can download the processed image by clicking on the "Download Result" link. | |
| ## Installation | |
| To run ImageMagic locally, follow these steps: | |
| 1. Clone this repository to your local machine: | |
| ``` | |
| git clone https://github.com/codewithdark-git/ImageMagic.git | |
| ``` | |
| 2. Navigate to the project directory: | |
| ``` | |
| cd ImageMagic | |
| ``` | |
| 3. Install the required dependencies: | |
| ``` | |
| pip install -r requirements.txt | |
| ``` | |
| 4. Run the Streamlit app: | |
| ``` | |
| streamlit run app.py | |
| ``` | |
| 5. Access the app in your web browser at `http://localhost:8501`. | |
| ## Credits | |
| - This app utilizes the [rembg](https://github.com/danielgatis/rembg) library for background removal. | |
| - Built with [Streamlit](https://streamlit.io/). | |
| ## License | |
| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | |
| """ | |
| st.markdown(readme_content) | |
| elif selected_option == "Home": | |
| st.subheader("Home") | |
| st.write("## Welcome to Image Processing App") | |
| st.write("This app allows you to perform various image processing tasks such as background removal and converting images to pencil sketches.") | |
| # Introduction to Background Removal | |
| st.write("### Background Removal") | |
| st.write("With the background removal feature, you can easily separate the main object from its background.") | |
| st.write("Here's an example of an original image and its background removed version:") | |
| # Display original image and background removed image | |
| st.write("### Original Image and Background Removed") | |
| st.write('<div style="display: flex;">', unsafe_allow_html=True) | |
| with st.container(): | |
| st.image("Background_remove.png", caption="Original Image", width=600) | |
| st.write('</div>', unsafe_allow_html=True) | |
| # Introduction to Pencil Sketch Conversion | |
| st.write("### Pencil Sketch Conversion") | |
| st.write("The app also provides an option to convert images into pencil sketches using OpenCV.") | |
| st.write("Here's an example of an original image and its corresponding pencil sketch:") | |
| # Display original image and pencil sketch image | |
| st.write("### Original Image and Pencil Sketch") | |
| st.write('<div style="display: flex;">', unsafe_allow_html=True) | |
| with st.container(): | |
| st.image("pencil_sketch.png", caption="Original Image", width=600) | |
| st.write('</div>', unsafe_allow_html=True) | |
| # Summarize the App | |
| st.write("### Summary") | |
| st.write("This app offers a simple yet powerful interface for performing common image processing tasks.") | |
| st.write("Explore the various functionalities and unleash your creativity!") | |
| # Footer with Author Information | |
| st.write("---") | |
| st.write("### About the Author") | |
| st.write("This app was created by Dark Coder.") | |
| st.write("For more projects and contact information, visit:") | |
| st.write("[GitHub](https://github.com/codewithdark-git) | [LinkedIn](https://www.linkedin.com/in/codewithdark)") | |
| elif selected_option == "Search image": | |
| st.title("") # No title for the search image section | |
| search_query = st.text_input("Enter search query:") | |
| if st.button("Search"): | |
| if search_query: | |
| search_unsplash_images(search_query) | |
| else: | |
| st.warning("Please enter a search query.") | |
| else: | |
| # Process uploaded image | |
| my_upload = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"]) | |
| if my_upload is not None: | |
| if my_upload.size > MAX_FILE_SIZE: | |
| st.error("The uploaded file is too large. Please upload an image smaller than 5MB.") | |
| else: | |
| process_image(upload=my_upload, action=selected_option) | |