update fix #2

app.py

@@ -9,7 +9,6 @@ decoder = load_model("models/decoder.h5")
 
 latent_dim = 128 
 
-img_size = (224, 224)
 
 def add_gaussian_noise(image, noise_factor=0.2):
     noisy_image = image + noise_factor * np.random.normal(size=image.shape)
@@ -17,16 +16,13 @@ def add_gaussian_noise(image, noise_factor=0.2):
     return noisy_image
 
 def denoise_and_generate(image, num_images):
-    # Redimensionar la imagen al tamaño esperado
-    image = cv2.resize(np.array(image), img_size) / 255.0  # Normalizar a [0,1]
-
-    noisy_image = add_gaussian_noise(np.expand_dims(image, axis=0))  # Añadir ruido
-
+    image = np.array(image) / 255.0
+    image = tf.image.resize(image, (224, 224))  # Redimensionar la imagen
+    noisy_image = add_gaussian_noise(np.expand_dims(image, axis=0))
+    
     denoised_image = autoencoder.predict(noisy_image).squeeze()
-    denoised_image = (denoised_image * 255).astype(np.uint8)  # Convertir a uint8
+    denoised_image = (denoised_image * 255).astype(np.uint8)
     
-    noisy_image_display = (noisy_image.squeeze() * 255).astype(np.uint8)  # Convertir a uint8
-
     # Genera imágenes con el VAE
     random_latent_vectors = np.random.normal(size=(num_images, latent_dim))
     generated_images = decoder.predict(random_latent_vectors)
@@ -36,6 +32,7 @@ def denoise_and_generate(image, num_images):
     
     return outputs
 
+
 # Define la interfaz
 inputs = [
     gr.Image(label="Imagen de Entrada"),
@@ -60,4 +57,4 @@ interface = gr.Interface(
 
 # Lanza la aplicación
 if __name__ == "__main__":
-    interface.launch(share=True)
+    interface.launch(share=True)