def deblur(weight_path, input_dir, output_dir):
g = generator_model()
g.load_weights(weight_path)
for image_name in os.listdir(input_dir):
image = np.array([preprocess_image(load_image(os.path.join(input_dir, image_name)))])
x_test = image
generated_images = g.predict(x=x_test)
generated = np.array([deprocess_image(img) for img in generated_images])
x_test = deprocess_image(x_test)
for i in range(generated_images.shape[0]):
x = x_test[i, :, :, :]
img = generated[i, :, :, :]
output = np.concatenate((x, img), axis=1)
im = Image.fromarray(output.astype(np.uint8))
im.save(os.path.join(output_dir, image_name))
def deblur(image_path):
data = {
'A_paths': [image_path],
'A': np.array([preprocess_image(load_image(image_path))])
}
x_test = data['A']
g = generator_model()
g.load_weights('generator.h5')
generated_images = g.predict(x=x_test)
generated = np.array([deprocess_image(img) for img in generated_images])
x_test = deprocess_image(x_test)
for i in range(generated_images.shape[0]):
x = x_test[i, :, :, :]
img = generated[i, :, :, :]
output = np.concatenate((x, img), axis=1)
im = Image.fromarray(output.astype(np.uint8))
im.save('deblur'+image_path)