Upload image_sharpner.py

image_sharpner.py

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+import streamlit as st
+import cv2
+import numpy as np
+from PIL import Image
+import io
+import os
+
+# Function to sharpen the image
+def sharpen_image(image, strength):
+    kernel = np.array([[0, -strength, 0],
+                       [-strength, 1 + 4 * strength, -strength],
+                       [0, -strength, 0]])
+    sharpened = cv2.filter2D(image, -1, kernel)
+    return sharpened
+
+# Function to smooth the image
+def smooth_image(image, strength):
+    ksize = int(2 * round(strength) + 1)  # Kernel size must be odd
+    smoothed = cv2.GaussianBlur(image, (ksize, ksize), 0)
+    return smoothed
+
+# Streamlit App
+st.title("Image Sharpening and Smoothing Tool")
+
+# File uploader
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+if uploaded_file:
+    # Read the uploaded image
+    original_name = os.path.splitext(uploaded_file.name)[0]  # Extract file name without extension
+    image = Image.open(uploaded_file)
+    image_array = np.array(image)
+
+    # Display the original image
+    st.subheader("Original Image")
+    st.image(image_array, channels="RGB")
+
+    # Choose between sharpening or smoothing
+    choice = st.radio("Choose an option:", ["Sharpen", "Smooth"])
+
+    # Slider for strength adjustment
+    if choice == "Sharpen":
+        strength = st.slider("Sharpening Strength", min_value=0.0, max_value=2.0, value=0.5, step=0.1)
+        processed_image = sharpen_image(image_array, strength)
+        suffix = "_sharpened"
+    else:
+        strength = st.slider("Smoothing Strength", min_value=1.0, max_value=10.0, value=3.0, step=1.0)
+        processed_image = smooth_image(image_array, strength)
+        suffix = "_smoothed"
+
+    # Display the processed image
+    st.subheader("Processed Image")
+    st.image(processed_image, channels="RGB")
+
+    # Convert the processed image to PIL format for downloading
+    processed_pil_image = Image.fromarray(processed_image)
+    if processed_pil_image.mode != "RGB":
+        processed_pil_image = processed_pil_image.convert("RGB")
+
+    # Prepare the image for download
+    buffer = io.BytesIO()
+    processed_pil_image.save(buffer, format="JPEG")
+    buffer.seek(0)
+
+    # Set the download filename
+    download_filename = f"{original_name}{suffix}.jpg"
+
+    # Download button
+    st.download_button(
+        label="Download Processed Image",
+        data=buffer,
+        file_name=download_filename,
+        mime="image/jpeg"
+    )