Update app.py

app.py

@@ -3,15 +3,32 @@ import numpy as np
 from PIL import Image
 from skimage.util import random_noise
 from skimage.restoration import denoise_nl_means, estimate_sigma
+import hashlib
 
-def add_noise(image, mean, var):
+def hash_password(password):
+    """Hash the password to generate noise parameters."""
+    hash_object = hashlib.sha256(password.encode())
+    hex_dig = hash_object.hexdigest()
+    return int(hex_dig, 16)
+
+def add_noise(image, password):
+    """Add Gaussian noise to the image based on the password."""
+    seed = hash_password(password) % (2**32)
+    np.random.seed(seed)
+    mean = np.random.uniform(-0.05, 0.05)
+    var = np.random.uniform(0.001, 0.01)
     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)  # Scale back to 0-255
     return Image.fromarray(noisy_image)
 
-def remove_noise(image):
-    image = image.convert('L')
+def remove_noise(noisy_image, password):
+    """Attempt to remove noise from the image using the same password."""
+    seed = hash_password(password) % (2**32)
+    np.random.seed(seed)  # Reset the seed to generate the same noise parameters
+    mean = np.random.uniform(-0.05, 0.05)
+    var = np.random.uniform(0.001, 0.01)
+    image = noisy_image.convert('L')
     image_np = np.array(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,
@@ -19,18 +36,24 @@ def remove_noise(image):
     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"),
-        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")
-    ],
-    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."
-)
+# Define Gradio interface with tabs for adding and removing noise
+with gr.Blocks() as interface:
+    gr.Markdown("### Image Noise Encryption and Decryption App")
+    with gr.Tab("Encrypt"):
+        with gr.Row():
+            image_input = gr.Image(label="Original Image")
+            password_input = gr.Textbox(label="Password for Encryption", placeholder="Enter a strong password", type="password")
+            encrypt_button = gr.Button("Encrypt Image")
+        image_output = gr.Image(label="Encrypted Image")
+        encrypt_button.click(add_noise, inputs=[image_input, password_input], outputs=image_output)
+
+    with gr.Tab("Decrypt"):
+        with gr.Row():
+            image_input_decrypt = gr.Image(label="Encrypted Image")
+            password_input_decrypt = gr.Textbox(label="Password for Decryption", placeholder="Enter the same password used for encryption", type="password")
+            decrypt_button = gr.Button("Decrypt Image")
+        image_output_decrypt = gr.Image(label="Decrypted Image")
+        decrypt_button.click(remove_noise, inputs=[image_input_decrypt, password_input_decrypt], outputs=image_output_decrypt)
 
 # Launch the app
-interface.launch()
+interface.launch()