Update app.py

app.py

@@ -7,7 +7,7 @@ from skimage.restoration import denoise_nl_means, estimate_sigma
 def add_noise(image, mean, var):
     sigma = var ** 0.5
     noisy_image = random_noise(np.array(image), mode='gaussian', mean=mean, var=var)
-    noisy_image = (255 * noisy_image).astype(np.uint8)
+    noisy_image = (255 * noisy_image).astype(np.uint8)  # Scale back to 0-255
     return Image.fromarray(noisy_image)
 
 def remove_noise(image):
@@ -16,17 +16,21 @@ def remove_noise(image):
     sigma_est = np.mean(estimate_sigma(image_np, multichannel=False))
     denoised_image = denoise_nl_means(image_np, h=1.15 * sigma_est, fast_mode=True,
                                       patch_size=5, patch_distance=6, multichannel=False)
-    denoised_image = (255 * denoised_image).astype(np.uint8)
+    denoised_image = (255 * denoised_image).astype(np.uint8)  # Scale back to 0-255
     return Image.fromarray(denoised_image)
 
+# Define Gradio interface
 interface = gr.Interface(
     fn=add_noise,
-    inputs=[gr.Image(label="Original Image"), 
+    inputs=[
+        gr.Image(label="Original Image"),
         gr.Slider(0, 0.05, step=0.001, value=0, label="Mean of Gaussian Noise"),
-        gr.Slider(0, 0.01, step=0.0001, value=0.001, label="Variance of Gaussian Noise"),
+        gr.Slider(0, 0.01, step=0.0001, value=0.001, label="Variance of Gaussian Noise")
+    ],
     outputs=gr.Image(label="Processed Image"),
     title="Image Noise Addition and Removal",
     description="Add Gaussian noise to an image and attempt to remove it. Adjust the mean and variance for different effects."
 )
 
+# Launch the app
 interface.launch()