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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"
)
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