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Franco Astegiano
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db9e08e
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Parent(s):
67eb3ce
Update tf_hub_fast_style_transfer_for_arbitrary_styles.py
Browse files
examples/colab/tf_hub_fast_style_transfer_for_arbitrary_styles.py
CHANGED
@@ -107,12 +107,15 @@ def show_n(images, titles=('',)):
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plt.title(titles[i] if len(titles) > i else '')
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plt.show()
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"""Let's get as well some images to play with."""
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# @title Load example images { display-mode: "form" }
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content_image_url = 'https://live.staticflickr.com/65535/52032998695_f57c61746c_c.jpg' # @param {type:"string"}
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style_image_url = 'https://live.staticflickr.com/65535/52032731604_a815a0b19f_c.jpg' # @param {type:"string"}
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output_image_size = 384 # @param {type:"integer"}
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# The content image size can be arbitrary.
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@@ -122,8 +125,16 @@ content_img_size = (output_image_size, output_image_size)
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# well but will lead to different results).
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style_img_size = (256, 256) # Recommended to keep it at 256.
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style_image = tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME')
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show_n([content_image, style_image], ['Content image', 'Style image'])
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@@ -155,6 +166,10 @@ is the same as the content image shape.
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# This is pretty fast within a few milliseconds on a GPU.
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def modify(imageinput,style_input):
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outputs = hub_module(tf.constant(imageinput), tf.constant(style_input))
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return outputs[0]
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#stylized_image = outputs[0]
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@@ -165,8 +180,6 @@ def modify(imageinput,style_input):
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# Gradio app
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content_image_input = gr.inputs.Image(label="Content Image")
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style_image_input = gr.inputs.Image(shape=(256, 256), label="Style Image")
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app_interface = gr.Interface(modify,
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inputs=[content_image_input, style_image_input],
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plt.title(titles[i] if len(titles) > i else '')
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plt.show()
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"""Let's get as well some images to play with."""
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# @title Load example images { display-mode: "form" }
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#content_image_url = 'https://live.staticflickr.com/65535/52032998695_f57c61746c_c.jpg' # @param {type:"string"}
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#style_image_url = 'https://live.staticflickr.com/65535/52032731604_a815a0b19f_c.jpg' # @param {type:"string"}
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output_image_size = 384 # @param {type:"integer"}
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# The content image size can be arbitrary.
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# well but will lead to different results).
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style_img_size = (256, 256) # Recommended to keep it at 256.
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# Load images from app
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content_image_input = gr.inputs.Image(label="Content Image")
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style_image_input = gr.inputs.Image(shape=(256, 256), label="Style Image")
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content_image = load_image(content_image_input, content_img_size)
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style_image = load_image(style_image_input, style_img_size)
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style_image = tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME')
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show_n([content_image, style_image], ['Content image', 'Style image'])
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# This is pretty fast within a few milliseconds on a GPU.
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def modify(imageinput,style_input):
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content_image = load_image(imageinput, content_img_size)
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style_image = load_image(style_input, style_img_size)
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style_image = tf.nn.avg_pool(style_image, ksize=[3,3], strides=[1,1], padding='SAME')
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#show_n([content_image, style_image], ['Content image', 'Style image'])
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outputs = hub_module(tf.constant(imageinput), tf.constant(style_input))
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return outputs[0]
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#stylized_image = outputs[0]
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# Gradio app
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app_interface = gr.Interface(modify,
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inputs=[content_image_input, style_image_input],
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