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''' |
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Neural Style Transfer using TensorFlow's Pretrained Style Transfer Model |
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https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2 |
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''' |
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import gradio as gr |
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import tensorflow as tf |
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import tensorflow_hub as hub |
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from PIL import Image |
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import numpy as np |
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import cv2 |
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import os |
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model = hub.load("https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2") |
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def unsharp_mask(image, kernel_size=(5, 5), sigma=1.0, amount=1.0, threshold=0): |
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"""Return a sharpened version of the image, using an unsharp mask.""" |
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blurred = cv2.GaussianBlur(image, kernel_size, sigma) |
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sharpened = float(amount + 1) * image - float(amount) * blurred |
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sharpened = np.maximum(sharpened, np.zeros(sharpened.shape)) |
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sharpened = np.minimum(sharpened, 255 * np.ones(sharpened.shape)) |
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sharpened = sharpened.round().astype(np.uint8) |
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if threshold > 0: |
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low_contrast_mask = np.absolute(image - blurred) < threshold |
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np.copyto(sharpened, image, where=low_contrast_mask) |
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return sharpened |
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def style_transfer(content_img,style_image, style_weight = 1, content_weight = 1, style_blur=False): |
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content_img = unsharp_mask(content_img,amount=1) |
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content_img = tf.image.resize(tf.convert_to_tensor(content_img,tf.float32)[tf.newaxis,...] / 255.,(512,512),preserve_aspect_ratio=True) |
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style_img = tf.convert_to_tensor(style_image,tf.float32)[tf.newaxis,...] / 255. |
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if style_blur: |
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style_img= tf.nn.avg_pool(style_img, [3,3], [1,1], "VALID") |
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style_img = tf.image.adjust_contrast(style_img, style_weight) |
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content_img = tf.image.adjust_contrast(content_img,content_weight) |
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content_img = tf.image.adjust_saturation(content_img, 2) |
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content_img = tf.image.adjust_contrast(content_img,1.5) |
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stylized_img = model(content_img, style_img)[0] |
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return Image.fromarray(np.uint8(stylized_img[0]*255)) |
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title = "PixelFusion🧬" |
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description = "Gradio Demo for Artistic Neural Style Transfer. To use it, simply upload a content image and a style image. [Learn More](https://www.tensorflow.org/tutorials/generative/style_transfer)." |
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article = "</br><p style='text-align: center'><a href='https://github.com/0xsynapse' target='_blank'>GitHub</a></p> " |
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content_input = gr.inputs.Image(label="Upload Your Image ",) |
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style_input = gr.inputs.Image( label="Upload Style Image ",shape= (256,256), ) |
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style_slider = gr.inputs.Slider(0,2,label="Adjust Style Density" ,default=1,) |
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content_slider = gr.inputs.Slider(1,5,label="Content Sharpness" ,default=1,) |
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examples = [ |
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["Content/content_1.jpg","Styles/style_1.jpg",1.20,1.70,"style_checkbox"], |
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["Content/content_2.jpg","Styles/style_2.jpg",0.91,2.54,"style_checkbox"], |
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["Content/content_3.png","Styles/style_3.jpg",1.02,2.47,"style_checkbox"] |
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] |
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interface = gr.Interface(fn=style_transfer, |
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inputs=[content_input, |
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style_input, |
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style_slider , |
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content_slider, |
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], |
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outputs=gr.outputs.Image(type="pil"), |
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title=title, |
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description=description, |
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article=article, |
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examples=examples, |
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enable_queue=True |
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) |
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interface.launch() |
