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import streamlit as st | |
import numpy as np | |
from scipy.ndimage import gaussian_filter | |
def main(): | |
st.title("Image Denoising with Diffusion") | |
uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png"]) | |
if uploaded_image: | |
image_array = np.array(uploaded_image) | |
denoised_image = apply_diffusion(image_array) | |
st.image(denoised_image, caption="Denoised Image", use_column_width=True) | |
if __name__ == "__main__": | |
main() | |
def apply_diffusion(image_array): | |
# Convert to grayscale if needed | |
if len(image_array.shape) == 3: | |
image_array = np.mean(image_array, axis=2) | |
# Apply Gaussian diffusion | |
denoised_image = gaussian_filter(image_array, sigma=1.0) | |
return denoised_image | |