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import tensorflow as tf
import tensorflow_hub as hub
import numpy as np
import gradio as gr
import cv2
# Carrega o modelo de transferência de estilo pré-treinado
style_transfer_model = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
def load_image(image):
# Função para processar a imagem para o modelo
image = image.astype(np.float32)[np.newaxis, ...] / 255.
if image.shape[-1] == 4:
image = image[..., :3]
return image
def interpolate_images(baseline, target, alpha):
return baseline + alpha * (target - baseline)
def apply_sharpness(image, intensity):
kernel = np.array([[0, -intensity, 0],
[-intensity, 1 + 4 * intensity, -intensity],
[0, -intensity, 0]])
sharp_image = cv2.filter2D(image, -1, kernel)
return np.clip(sharp_image, 0, 255)
def style_transfer(content_image, style_image, style_density, content_sharpness):
# Processa as imagens
content_image = load_image(content_image)
style_image = load_image(style_image)
# Aplica nitidez na imagem de conteúdo antes da transferência de estilo
content_image_sharp = apply_sharpness(content_image[0], intensity=content_sharpness)
content_image_sharp = content_image_sharp[np.newaxis, ...]
# Executa a transferência de estilo
stylized_image = style_transfer_model(tf.constant(content_image_sharp), tf.constant(style_image))[0]
# Interpola entre a imagem de conteúdo e a imagem estilizada para densidade de estilo
stylized_image = interpolate_images(
baseline=content_image[0],
target=stylized_image.numpy(),
alpha=style_density
)
# Converte a imagem resultante para o formato correto
stylized_image = np.array(stylized_image * 255, np.uint8)
# Remove a dimensão do batch
stylized_image = np.squeeze(stylized_image)
return stylized_image
iface = gr.Interface(
fn=style_transfer,
inputs=[
gr.Image(label="Content Image"), # Imagem de conteúdo
gr.Image(label="Style Image"), # Imagem de estilo
gr.Slider(minimum=0, maximum=1, value=0.5, label="Adjust Style Density"),
gr.Slider(minimum=0, maximum=1, value=0.5, label="Content Sharpness")
],
outputs=gr.Image(label="Stylized Image")
)
iface.launch()
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