| | import numpy as np |
| | from PIL import Image |
| | from skimage.util import random_noise |
| |
|
| | |
| | dimensiones = (256, 256) |
| |
|
| | |
| | def normalize_image(img): |
| | """ |
| | Normaliza una imagen PIL a valores entre [0,1] y la redimensiona a (256,256). |
| | """ |
| | img = img.resize(dimensiones) |
| | img_array = np.array(img, dtype=np.float32) / 255.0 |
| | return img_array |
| |
|
| | |
| | def add_gaussian_noise(img_array): |
| | """ |
| | Añade ruido gaussiano a una imagen normalizada en el rango [0,1]. |
| | """ |
| | img_noisy = random_noise(img_array, mode='gaussian', mean=0, var=0.3) |
| | return img_noisy |
| |
|
| | |
| | def preprocess_single_image(img): |
| | """ |
| | Toma una imagen PIL, la normaliza y le añade ruido, devolviendo ambas versiones. |
| | """ |
| | img_clean = normalize_image(img) |
| | img_noisy = add_gaussian_noise(img_clean) |
| |
|
| | return img_noisy, img_clean |
| |
|