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| """Application to demo inpainting, Median and Bilateral Blur using streamlit. | |
| Run using: streamlit run 10_04_image_restoration_app.py | |
| """ | |
| import streamlit as st | |
| import pathlib | |
| from streamlit_drawable_canvas import st_canvas | |
| import cv2 | |
| import numpy as np | |
| import io | |
| import base64 | |
| from PIL import Image | |
| # # Function to create a download link for output image | |
| # def get_image_download_link(img, filename, text): | |
| # """Generates a link to download a particular image file.""" | |
| # buffered = io.BytesIO() | |
| # img.save(buffered, format='JPEG') | |
| # img_str = base64.b64encode(buffered.getvalue()).decode() | |
| # href = f'<a href="data:file/txt;base64,{img_str}" download="{filename}">{text}</a>' | |
| # return href | |
| # Set title. | |
| st.sidebar.title('Image Restoration App with OpenCV') | |
| # Description | |
| st.sidebar.text('Upload an image and apply various restoration techniques.') | |
| # Specify canvas parameters in application | |
| uploaded_file = st.sidebar.file_uploader("Upload Image to restore:", type=["png", "jpg"]) | |
| image = None | |
| res = None | |
| if uploaded_file is not None: | |
| # Convert the file to an opencv image. | |
| file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8) | |
| image = cv2.imdecode(file_bytes, 1) | |
| # Display the uploaded image | |
| st.subheader("Original Image") | |
| st.image(image[:, :, ::-1]) | |
| # Display a selection box for choosing the filter to apply. | |
| option = st.sidebar.selectbox('Median or Bilateral Blur or Inpaint?', ('None', 'Median Blur', 'Bilateral Blur', 'Image Inpaint')) | |
| if option == 'Median Blur': | |
| ksize = st.sidebar.slider("ksize: ", 3, 15, 5, 2) | |
| image = cv2.medianBlur(image, ksize) | |
| res=image[:,:,::-1] | |
| st.subheader("Median Blurred Image") | |
| st.image(res) | |
| # Display download button | |
| result = Image.fromarray(res) | |
| buffered = io.BytesIO() | |
| result.save(buffered, format="PNG") | |
| img_bytes = buffered.getvalue() | |
| st.download_button(label='Download Output', data=img_bytes, file_name='median_blur_output.png', mime='image/png') | |
| elif option == 'Bilateral Blur': | |
| dia = st.sidebar.slider("diameter: ", 1, 50, 20) | |
| sigmaColor = st.sidebar.slider("sigmaColor: ", 0, 250, 200, 10) | |
| sigmaSpace = st.sidebar.slider("sigmaSpace: ", 0, 250, 100, 10) | |
| image = cv2.bilateralFilter(image, dia, sigmaColor, sigmaSpace) | |
| res=image[:,:,::-1] | |
| st.subheader("Bilateral Blurred Image") | |
| st.image(res) | |
| # Display download button | |
| result = Image.fromarray(res) | |
| buffered = io.BytesIO() | |
| result.save(buffered, format="PNG") | |
| img_bytes = buffered.getvalue() | |
| st.download_button(label='Download Output', data=img_bytes, file_name='bilateral_blur_output.png', mime='image/png') | |
| elif option == 'Image Inpaint': | |
| stroke_width = st.sidebar.slider("Stroke width: ", 1, 25, 5) | |
| h, w = image.shape[:2] | |
| if w > 800: | |
| h_, w_ = int(h * 800 / w), 800 | |
| else: | |
| h_, w_ = h, w | |
| # Create a canvas component. | |
| st.subheader("Draw over the areas you want to inpaint:") | |
| canvas_result = st_canvas( | |
| fill_color='white', | |
| stroke_width=stroke_width, | |
| stroke_color='black', | |
| background_image=Image.open(uploaded_file).resize((h_, w_)), | |
| update_streamlit=True, | |
| height=h_, | |
| width=w_, | |
| drawing_mode='freedraw', | |
| key="canvas", | |
| ) | |
| stroke = canvas_result.image_data | |
| if stroke is not None: | |
| if st.sidebar.checkbox('show mask'): | |
| st.subheader("Mask") | |
| st.image(stroke) | |
| mask = cv2.split(stroke)[3] | |
| mask = np.uint8(mask) | |
| mask = cv2.resize(mask, (w, h)) | |
| st.sidebar.caption('Happy with the selection?') | |
| option = st.sidebar.selectbox('Mode', ['None', 'Telea', 'NS', 'Compare both']) | |
| if option == 'Telea': | |
| st.subheader('Result of Telea') | |
| res = cv2.inpaint(src=image, inpaintMask=mask, inpaintRadius=3, flags=cv2.INPAINT_TELEA)[:,:,::-1] | |
| st.image(res) | |
| # Display download button | |
| result = Image.fromarray(res) | |
| buffered = io.BytesIO() | |
| result.save(buffered, format="PNG") | |
| img_bytes = buffered.getvalue() | |
| st.download_button(label='Download Output', data=img_bytes, file_name='inpaint_telea_output.png', mime='image/png') | |
| elif option == 'Compare both': | |
| col1, col2 = st.columns(2) | |
| res1 = cv2.inpaint(src=image, inpaintMask=mask, inpaintRadius=3, flags=cv2.INPAINT_TELEA)[:,:,::-1] | |
| res2 = cv2.inpaint(src=image, inpaintMask=mask, inpaintRadius=3, flags=cv2.INPAINT_NS)[:,:,::-1] | |
| with col1: | |
| st.subheader('Result of Telea') | |
| st.image(res1) | |
| # Display download button | |
| result1 = Image.fromarray(res1) | |
| buffered1 = io.BytesIO() | |
| result1.save(buffered1, format="PNG") | |
| img_bytes1 = buffered1.getvalue() | |
| st.download_button(label='Download Output', data=img_bytes1, file_name='inpaint_telea_output.png', mime='image/png') | |
| with col2: | |
| st.subheader('Result of NS') | |
| st.image(res2) | |
| # Display download button | |
| result2 = Image.fromarray(res2) | |
| buffered2 = io.BytesIO() | |
| result2.save(buffered2, format="PNG") | |
| img_bytes2 = buffered2.getvalue() | |
| st.download_button(label='Download Output', data=img_bytes2, file_name='inpaint_ns_output.png', mime='image/png') | |
| elif option == 'NS': | |
| st.subheader('Result of NS') | |
| res = cv2.inpaint(src=image, inpaintMask=mask, inpaintRadius=3, flags=cv2.INPAINT_NS)[:,:,::-1] | |
| st.image(res) | |
| # Display download button | |
| result = Image.fromarray(res) | |
| buffered = io.BytesIO() | |
| result.save(buffered, format="PNG") | |
| img_bytes = buffered.getvalue() | |
| st.download_button(label='Download Output', data=img_bytes, file_name='inpaint_ns_output.png', mime='image/png') | |
| else: | |
| pass | |