Sa-m commited on
Commit
0fa9601
·
1 Parent(s): 4fe3e06

Update app.py

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Files changed (1) hide show
  1. app.py +4 -20
app.py CHANGED
@@ -2,7 +2,6 @@
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  import gradio as gr
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  import tensorflow as tf
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- # import os
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  import tensorflow_hub as hub
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  import PIL
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  from PIL import Image,ImageOps
@@ -38,25 +37,9 @@ def tensor_to_image(tensor):
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  tensor = tensor[0]
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  return PIL.Image.fromarray(tensor)
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- """##Saving unscaled Tensor images."""
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-
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- def save_image(image, filename):
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- """
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- Saves unscaled Tensor Images.
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- Args:
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- image: 3D image tensor. [height, width, channels]
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- filename: Name of the file to save to.
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- """
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- if not isinstance(image, Image.Image):
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- image = tf.clip_by_value(image, 0, 255)
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- image = Image.fromarray(tf.cast(image, tf.uint8).numpy())
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- image.save("%s.jpg" % filename)
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- print("Saved as %s.jpg" % filename)
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-
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- """## Grayscaling image for testing purpose to check if we could get better results."""
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-
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  def gray_scaled(inp_img):
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  gray = cv2.cvtColor(inp_img, cv2.COLOR_BGR2GRAY)
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  gray_img = np.zeros_like(inp_img)
@@ -65,6 +48,7 @@ def gray_scaled(inp_img):
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  gray_img[:,:,2] = gray
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  return gray_img
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  def transform_mymodel(content_image,style_image):
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  # Convert to float32 numpy array, add batch dimension, and normalize to range [0, 1]
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  #content_image=gray_scaled(content_image)
@@ -86,8 +70,8 @@ def gradio_intrface(mymodel):
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  # Initializing the input component
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  image1 = gr.inputs.Image(label="Content Image") #CONTENT IMAGE
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  image2 = gr.inputs.Image(label="Style Image") #STYLE IMAGE
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- stylizedimg=gr.outputs.Image()
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- gr.Interface(fn=mymodel, inputs= [image1,image2] , outputs= stylizedimg,title='Style Transfer',theme='seafoam',examples=[['Content_Images/contnt12.jpg','VG516.jpg']],article="**References**\n\n""<a href='https://www.tensorflow.org/hub/tutorials/tf2_arbitrary_image_stylization'</a>\n").launch()
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  """The function will be launched both Inline and Outline where u need to add a content and style image."""
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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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  import PIL
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  from PIL import Image,ImageOps
 
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  tensor = tensor[0]
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  return PIL.Image.fromarray(tensor)
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+ """## Grayscaling image for testing purpose to check if we could get better results."""
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  def gray_scaled(inp_img):
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  gray = cv2.cvtColor(inp_img, cv2.COLOR_BGR2GRAY)
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  gray_img = np.zeros_like(inp_img)
 
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  gray_img[:,:,2] = gray
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  return gray_img
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+ ##Transformation
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  def transform_mymodel(content_image,style_image):
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  # Convert to float32 numpy array, add batch dimension, and normalize to range [0, 1]
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  #content_image=gray_scaled(content_image)
 
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  # Initializing the input component
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  image1 = gr.inputs.Image(label="Content Image") #CONTENT IMAGE
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  image2 = gr.inputs.Image(label="Style Image") #STYLE IMAGE
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+ stylizedimg=gr.outputs.Image(label="Result")
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+ gr.Interface(fn=mymodel, inputs= [image1,image2] , outputs= stylizedimg,title='Style Transfer',theme='seafoam',examples=[['Content_Images/contnt12.jpg','VG516.jpg']],article="References-\n\n""<a href='https://www.tensorflow.org/hub/tutorials/tf2_arbitrary_image_stylization'>\n").launch()
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  """The function will be launched both Inline and Outline where u need to add a content and style image."""
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