|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
'''NEURAL STYLE TRANSFER ''' |
|
|
|
|
|
import numpy as np |
|
|
import tensorflow as tf |
|
|
import tensorflow_hub as hub |
|
|
import gradio as gr |
|
|
from PIL import Image |
|
|
import os |
|
|
import logging |
|
|
|
|
|
|
|
|
logging.basicConfig(level=logging.INFO) |
|
|
logger = logging.getLogger(__name__) |
|
|
|
|
|
np.set_printoptions(suppress=True) |
|
|
|
|
|
|
|
|
try: |
|
|
logger.info("Loading TensorFlow Hub model...") |
|
|
model = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2') |
|
|
logger.info("Model loaded successfully!") |
|
|
except Exception as e: |
|
|
logger.error(f"Error loading model: {str(e)}") |
|
|
raise |
|
|
|
|
|
def tensor_to_image(tensor): |
|
|
try: |
|
|
tensor *= 255 |
|
|
tensor = np.array(tensor, dtype=np.uint8) |
|
|
if tensor.ndim > 3: |
|
|
tensor = tensor[0] |
|
|
return Image.fromarray(tensor) |
|
|
except Exception as e: |
|
|
logger.error(f"Error in tensor_to_image: {str(e)}") |
|
|
raise |
|
|
|
|
|
def transform_my_model(content_image, style_image): |
|
|
try: |
|
|
if content_image is None or style_image is None: |
|
|
raise ValueError("Both content and style images are required") |
|
|
|
|
|
logger.info("Processing images...") |
|
|
content_image = content_image.astype(np.float32)[np.newaxis, ...] / 255.0 |
|
|
style_image = style_image.astype(np.float32)[np.newaxis, ...] / 255.0 |
|
|
stylized_image = model(tf.constant(content_image), tf.constant(style_image))[0] |
|
|
logger.info("Style transfer completed successfully!") |
|
|
return tensor_to_image(stylized_image) |
|
|
except Exception as e: |
|
|
logger.error(f"Error in transform_my_model: {str(e)}") |
|
|
raise |
|
|
|
|
|
|
|
|
example_images = [ |
|
|
["Content_Images/contnt12.jpg", "VG516.jpg"], |
|
|
["Content_Images/contnt2.jpg", "Content_Images/styl9.jpg"], |
|
|
["Content_Images/contnt.jpg", "Content_Images/styl22.jpg"] |
|
|
] |
|
|
|
|
|
valid_examples = [] |
|
|
for content_path, style_path in example_images: |
|
|
if os.path.exists(content_path) and os.path.exists(style_path): |
|
|
valid_examples.append([content_path, style_path]) |
|
|
else: |
|
|
logger.warning(f"Example image not found: {content_path} or {style_path}") |
|
|
|
|
|
demo = gr.Interface( |
|
|
fn=transform_my_model, |
|
|
inputs=[gr.Image(label="Content Image"), gr.Image(label="Style Image")], |
|
|
outputs=gr.Image(label="Result"), |
|
|
title="Neural Style Transfer", |
|
|
description="Upload a content image and a style image to create a stylized version of your content image.", |
|
|
examples=valid_examples if valid_examples else None, |
|
|
article="References-\n\nExploring the structure of a real-time, arbitrary neural artistic stylization network. Golnaz Ghiasi, Honglak Lee, Manjunath Kudlur, Vincent Dumoulin." |
|
|
) |
|
|
|
|
|
if __name__ == "__main__": |
|
|
demo.launch( |
|
|
server_name="0.0.0.0", |
|
|
server_port=7860, |
|
|
share=True, |
|
|
show_error=True |
|
|
) |
|
|
|
