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app.py

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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

requirements.txt

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+numpy
+streamlit
+streamlit_drawable_canvas
+opencv-python-headless
+pillow